End of training
Browse files- README.md +134 -0
- generation_config.json +7 -0
README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: EleutherAI/pythia-160m
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tags:
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- axolotl
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- generated_from_trainer
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datasets:
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- argilla/databricks-dolly-15k-curated-en
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model-index:
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- name: pythia-160m
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results: []
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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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[<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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axolotl version: `0.6.0`
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```yaml
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base_model: EleutherAI/pythia-160m
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batch_size: 120
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bf16: true
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chat_template: tokenizer_default_fallback_alpaca
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datasets:
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- format: custom
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path: argilla/databricks-dolly-15k-curated-en
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type:
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field_input: original-instruction
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field_instruction: original-instruction
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field_output: original-response
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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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device_map: auto
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eval_sample_packing: false
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eval_steps: 20
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flash_attention: true
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gradient_checkpointing: true
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group_by_length: true
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hub_model_id: SystemAdmin123/pythia-160m
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hub_strategy: checkpoint
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learning_rate: 0.0002
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logging_steps: 10
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lr_scheduler: cosine
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max_steps: 10000
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micro_batch_size: 30
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model_type: AutoModelForCausalLM
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num_epochs: 100
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optimizer: adamw_bnb_8bit
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output_dir: /root/.sn56/axolotl/tmp/pythia-160m
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pad_to_sequence_len: true
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resize_token_embeddings_to_32x: false
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sample_packing: true
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save_steps: 20
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save_total_limit: 1
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sequence_len: 2048
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special_tokens:
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pad_token: <|endoftext|>
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tokenizer_type: GPTNeoXTokenizerFast
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torch_dtype: bf16
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training_args_kwargs:
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hub_private_repo: true
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trust_remote_code: true
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val_set_size: 0.1
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wandb_entity: ''
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wandb_mode: online
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wandb_name: EleutherAI/pythia-160m-argilla/databricks-dolly-15k-curated-en
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wandb_project: Gradients-On-Demand
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wandb_run: your_name
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wandb_runid: default
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warmup_ratio: 0.05
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```
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</details><br>
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# pythia-160m
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This model is a fine-tuned version of [EleutherAI/pythia-160m](https://huggingface.co/EleutherAI/pythia-160m) on the argilla/databricks-dolly-15k-curated-en dataset.
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It achieves the following results on the evaluation set:
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- Loss: 6.8402
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 30
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- eval_batch_size: 30
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 4
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- total_train_batch_size: 120
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- total_eval_batch_size: 120
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- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 5
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- training_steps: 100
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-------:|:----:|:---------------:|
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| No log | 0.1667 | 1 | 3.8775 |
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| 7.7135 | 3.3333 | 20 | 7.3552 |
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| 7.4558 | 6.6667 | 40 | 7.1266 |
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| 6.9453 | 10.0 | 60 | 6.8628 |
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| 6.7644 | 13.3333 | 80 | 6.8403 |
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| 6.7186 | 16.6667 | 100 | 6.8402 |
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### Framework versions
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- Transformers 4.48.1
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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generation_config.json
ADDED
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@@ -0,0 +1,7 @@
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{
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"_from_model_config": true,
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"bos_token_id": 0,
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"do_sample": true,
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"eos_token_id": 0,
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"transformers_version": "4.48.1"
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}
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