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End of training

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README.md ADDED
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+ ---
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+ library_name: peft
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+ license: apache-2.0
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+ base_model: unsloth/SmolLM-360M-Instruct
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+ tags:
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+ - axolotl
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+ - generated_from_trainer
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+ model-index:
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+ - name: f263595e-91dc-4dbc-aee8-42a3b57e2dde
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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+ <details><summary>See axolotl config</summary>
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+
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+ axolotl version: `0.4.1`
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+ ```yaml
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+ adapter: lora
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+ base_model: unsloth/SmolLM-360M-Instruct
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+ bf16: auto
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+ chat_template: llama3
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+ dataset_prepared_path: null
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+ datasets:
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+ - data_files:
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+ - 902ecde58c94c532_train_data.json
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+ ds_type: json
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+ format: custom
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+ path: /workspace/input_data/902ecde58c94c532_train_data.json
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+ type:
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+ field_input: original_version
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+ field_instruction: title
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+ field_output: french_version
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+ format: '{instruction} {input}'
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+ no_input_format: '{instruction}'
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+ system_format: '{system}'
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+ system_prompt: ''
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+ debug: null
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+ deepspeed: null
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+ device_map: auto
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+ do_eval: true
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+ early_stopping_patience: 3
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+ eval_batch_size: 4
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+ eval_max_new_tokens: 128
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+ eval_steps: 300
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+ eval_table_size: null
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+ evals_per_epoch: null
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+ flash_attention: true
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+ fp16: false
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+ fsdp: null
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+ fsdp_config: null
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+ gradient_accumulation_steps: 4
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+ gradient_checkpointing: false
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+ group_by_length: true
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+ hub_model_id: robiulawaldev/f263595e-91dc-4dbc-aee8-42a3b57e2dde
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+ hub_strategy: end
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+ learning_rate: 0.0002
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+ load_in_4bit: false
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+ load_in_8bit: false
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+ local_rank: null
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+ logging_steps: 50
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+ lora_alpha: 64
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+ lora_dropout: 0.05
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+ lora_fan_in_fan_out: null
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+ lora_model_dir: null
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+ lora_r: 32
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+ lora_target_linear: true
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+ lr_scheduler: constant
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+ max_grad_norm: 1.0
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+ max_memory:
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+ 0: 75GB
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+ max_steps: 17953
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+ micro_batch_size: 4
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+ mlflow_experiment_name: /tmp/902ecde58c94c532_train_data.json
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+ model_type: AutoModelForCausalLM
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+ num_epochs: 10
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+ optim_args:
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+ adam_beta1: 0.9
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+ adam_beta2: 0.95
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+ adam_epsilon: 1e-5
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+ optimizer: adamw_bnb_8bit
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+ output_dir: miner_id_24
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+ pad_to_sequence_len: true
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+ resume_from_checkpoint: null
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+ s2_attention: null
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+ sample_packing: false
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+ save_steps: 300
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+ saves_per_epoch: null
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+ sequence_len: 512
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+ strict: false
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+ tf32: true
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+ tokenizer_type: AutoTokenizer
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+ train_on_inputs: false
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+ trust_remote_code: true
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+ val_set_size: 0.05
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+ wandb_entity: null
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+ wandb_mode: online
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+ wandb_name: fb292aae-3bf8-4614-82a9-5c9ce7b3f999
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+ wandb_project: SN56-36
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+ wandb_run: your_name
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+ wandb_runid: fb292aae-3bf8-4614-82a9-5c9ce7b3f999
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+ warmup_steps: 50
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+ weight_decay: 0.0
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+ xformers_attention: null
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+
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+ ```
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+
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+ </details><br>
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+
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+ # f263595e-91dc-4dbc-aee8-42a3b57e2dde
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+
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+ This model is a fine-tuned version of [unsloth/SmolLM-360M-Instruct](https://huggingface.co/unsloth/SmolLM-360M-Instruct) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9729
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 16
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+ - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5
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+ - lr_scheduler_type: constant
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+ - lr_scheduler_warmup_steps: 50
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+ - training_steps: 17953
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:-----:|:---------------:|
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+ | No log | 0.0002 | 1 | 2.4685 |
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+ | 1.6913 | 0.0510 | 300 | 1.6545 |
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+ | 1.5228 | 0.1021 | 600 | 1.5083 |
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+ | 1.4568 | 0.1531 | 900 | 1.4199 |
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+ | 1.3707 | 0.2042 | 1200 | 1.3690 |
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+ | 1.3347 | 0.2552 | 1500 | 1.3241 |
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+ | 1.2919 | 0.3063 | 1800 | 1.2925 |
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+ | 1.2462 | 0.3573 | 2100 | 1.2656 |
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+ | 1.2175 | 0.4083 | 2400 | 1.2438 |
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+ | 1.2624 | 0.4594 | 2700 | 1.2318 |
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+ | 1.216 | 0.5104 | 3000 | 1.2081 |
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+ | 1.2401 | 0.5615 | 3300 | 1.1880 |
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+ | 1.2172 | 0.6125 | 3600 | 1.1763 |
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+ | 1.1768 | 0.6635 | 3900 | 1.1606 |
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+ | 1.1733 | 0.7146 | 4200 | 1.1570 |
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+ | 1.1503 | 0.7656 | 4500 | 1.1437 |
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+ | 1.1261 | 0.8167 | 4800 | 1.1351 |
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+ | 1.124 | 0.8677 | 5100 | 1.1233 |
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+ | 1.1614 | 0.9188 | 5400 | 1.1161 |
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+ | 1.1346 | 0.9698 | 5700 | 1.1063 |
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+ | 1.0797 | 1.0208 | 6000 | 1.1005 |
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+ | 1.0431 | 1.0719 | 6300 | 1.0961 |
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+ | 1.0795 | 1.1229 | 6600 | 1.0894 |
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+ | 1.0587 | 1.1740 | 6900 | 1.0853 |
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+ | 1.0899 | 1.2250 | 7200 | 1.0778 |
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+ | 1.0412 | 1.2761 | 7500 | 1.0717 |
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+ | 1.0829 | 1.3271 | 7800 | 1.0683 |
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+ | 1.0652 | 1.3781 | 8100 | 1.0639 |
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+ | 1.0164 | 1.4292 | 8400 | 1.0583 |
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+ | 1.0589 | 1.4802 | 8700 | 1.0534 |
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+ | 1.0337 | 1.5313 | 9000 | 1.0461 |
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+ | 1.0161 | 1.5823 | 9300 | 1.0440 |
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+ | 1.0422 | 1.6333 | 9600 | 1.0420 |
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+ | 1.0025 | 1.6844 | 9900 | 1.0345 |
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+ | 0.9963 | 1.7354 | 10200 | 1.0337 |
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+ | 1.0322 | 1.7865 | 10500 | 1.0311 |
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+ | 1.0424 | 1.8375 | 10800 | 1.0278 |
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+ | 0.9842 | 1.8886 | 11100 | 1.0204 |
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+ | 0.9802 | 1.9396 | 11400 | 1.0150 |
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+ | 0.9941 | 1.9906 | 11700 | 1.0127 |
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+ | 0.9759 | 2.0417 | 12000 | 1.0113 |
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+ | 0.9635 | 2.0927 | 12300 | 1.0088 |
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+ | 0.941 | 2.1438 | 12600 | 1.0050 |
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+ | 0.9635 | 2.1948 | 12900 | 1.0041 |
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+ | 0.9709 | 2.2459 | 13200 | 1.0028 |
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+ | 0.9631 | 2.2969 | 13500 | 1.0006 |
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+ | 0.9533 | 2.3479 | 13800 | 0.9955 |
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+ | 0.9762 | 2.3990 | 14100 | 0.9941 |
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+ | 0.9899 | 2.4500 | 14400 | 0.9924 |
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+ | 0.9706 | 2.5011 | 14700 | 0.9898 |
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+ | 0.9315 | 2.5521 | 15000 | 0.9859 |
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+ | 0.9224 | 2.6031 | 15300 | 0.9868 |
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+ | 1.0113 | 2.6542 | 15600 | 0.9829 |
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+ | 0.9251 | 2.7052 | 15900 | 0.9817 |
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+ | 1.0008 | 2.7563 | 16200 | 0.9793 |
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+ | 0.9723 | 2.8073 | 16500 | 0.9787 |
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+ | 0.9673 | 2.8584 | 16800 | 0.9739 |
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+ | 0.9519 | 2.9094 | 17100 | 0.9714 |
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+ | 0.9699 | 2.9604 | 17400 | 0.9713 |
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+ | 0.93 | 3.0115 | 17700 | 0.9729 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.13.2
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+ - Transformers 4.46.0
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+ - Pytorch 2.5.0+cu124
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.1
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