End of training

README.md

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+---
+license: llama2
+base_model: meta-llama/Llama-2-7b-hf
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: Llama-2-7b-Alpaca52k
+  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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.4.0`
+```yaml
+base_model: meta-llama/Llama-2-7b-hf
+model_type: LlamaForCausalLM
+tokenizer_type: LlamaTokenizer
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: tatsu-lab/alpaca
+    type: alpaca
+    conversations: alpaca
+dataset_prepared_path: last_run_prepared
+val_set_size: 0.001
+output_dir: ./outputs/out_llama2_alpaca
+hub_model_id: flydust/Llama-2-7b-Alpaca52k
+
+sequence_len: 4096
+sample_packing: true
+eval_sample_packing: false
+pad_to_sequence_len: true
+
+wandb_project:
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+gradient_accumulation_steps: 4
+micro_batch_size: 2
+num_epochs: 4
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 2e-5
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+flash_attn_cross_entropy: false
+flash_attn_rms_norm: true
+flash_attn_fuse_qkv: false
+flash_attn_fuse_mlp: true
+
+warmup_ratio: 0.03
+evals_per_epoch: 3
+eval_table_size:
+saves_per_epoch: 1
+debug:
+weight_decay: 0.
+fsdp:
+fsdp_config:
+special_tokens:
+
+```
+
+</details><br>
+
+# Llama-2-7b-Alpaca52k
+
+This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9082
+
+## 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: 2e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- total_eval_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 6
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.3641        | 0.02   | 1    | 1.5519          |
+| 1.0767        | 0.34   | 17   | 0.9333          |
+| 1.0938        | 0.68   | 34   | 0.9166          |
+| 1.0373        | 1.02   | 51   | 0.9096          |
+| 1.0149        | 1.335  | 68   | 0.9031          |
+| 1.0084        | 1.675  | 85   | 0.9071          |
+| 0.9582        | 2.0150 | 102  | 0.9034          |
+| 0.9767        | 2.33   | 119  | 0.9066          |
+| 0.964         | 2.67   | 136  | 0.9060          |
+| 0.9334        | 3.01   | 153  | 0.9073          |
+| 0.9254        | 3.325  | 170  | 0.9084          |
+| 0.9295        | 3.665  | 187  | 0.9082          |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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