End of training

README.md

@@ -1,5 +1,164 @@
----
-license: other
-license_name: test-license
-license_link: LICENSE
----
+---
+base_model: mistralai/Mistral-7B-v0.1
+library_name: peft
+license: apache-2.0
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: mistral-test-alpaca
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<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)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.4.1`
+```yaml
+base_model: mistralai/Mistral-7B-v0.1
+model_type: MistralForCausalLM
+tokenizer_type: LlamaTokenizer
+is_mistral_derived_model: true
+
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+
+lora_fan_in_fan_out: false
+data_seed: 49
+seed: 49
+
+datasets:
+  - path: sample_data/alpaca_synth_queries.jsonl
+    type: sharegpt
+    conversation: alpaca
+
+dataset_prepared_path: last_run_prepared
+val_set_size: 0.1
+output_dir: ./ft-v1
+hub_model_id: mahendra0203/mistral-test-alpaca
+
+adapter: qlora
+lora_model_dir:
+sequence_len: 512  # Reduced from 896
+sample_packing: true  # Enable sample packing
+eval_sample_packing: false
+pad_to_sequence_len: false  # Changed to false
+
+lora_r: 16  # Reduced from 32
+lora_alpha: 32
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+lora_target_modules:
+  - gate_proj
+  - down_proj
+  - up_proj
+  - q_proj
+  - v_proj
+  - k_proj
+  - o_proj
+
+wandb_project: ft-alpaca-mistral-hc
+wandb_entity: mahendra0203
+
+gradient_accumulation_steps: 8  # Increased from 4
+micro_batch_size: 4  # Reduced from 16
+eval_batch_size: 4  # Reduced from 16
+num_epochs: 2
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.0002
+max_grad_norm: 1.0
+adam_beta2: 0.95
+adam_epsilon: 0.00001
+save_total_limit: 3  # Reduced from 12
+
+train_on_inputs: false
+group_by_length: true  # Changed to true
+bf16: true  # Changed to false
+fp16: false  # Changed to true
+tf32: false
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention: false
+flash_attention: false  
+
+loss_watchdog_threshold: 5.0
+loss_watchdog_patience: 3
+
+warmup_steps: 20
+evals_per_epoch: 2  # Reduced from 4
+eval_table_size:
+eval_table_max_new_tokens: 128
+saves_per_epoch: 2  # Reduced from 6
+debug:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+  bos_token: "<s>"
+  eos_token: "</s>"
+  unk_token: "<unk>"
+save_safetensors: true
+```
+
+</details><br>
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mahendra0203/ft-alpaca-mistral-hc/runs/yp7zk4y6)
+# mistral-test-alpaca
+
+This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3238
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 49
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 20
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.3818        | 0.6667 | 1    | 1.3490          |
+| 1.3841        | 1.1667 | 2    | 1.3238          |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.42.3
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1