End of training

README.md

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+---
+license: llama3
+library_name: peft
+tags:
+- axolotl
+- generated_from_trainer
+base_model: meta-llama/Meta-Llama-3-8B
+model-index:
+- name: llama-3-8b-lora-law2entity
+  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: `0.4.1`
+```yaml
+base_model: meta-llama/Meta-Llama-3-8B
+model_type: LlamaForCausalLM
+tokenizer_type: AutoTokenizer
+
+load_in_8bit: true
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: rubenamtz0/law_entity_recognition
+    type: alpaca
+dataset_prepared_path:
+val_set_size: 0.1
+output_dir: ./outputs/lora-law
+hub_model_id: rubenamtz0/llama-3-8b-lora-law2entity
+
+sequence_len: 4096
+sample_packing: true
+pad_to_sequence_len: true
+
+adapter: lora
+lora_model_dir:
+lora_r: 32
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+
+wandb_project: entity-relationship-claim-ft
+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: 0.0002
+
+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
+s2_attention:
+
+warmup_steps: 10
+evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+   pad_token: <|end_of_text|>
+
+```
+
+</details><br>
+
+# llama-3-8b-lora-law2entity
+
+This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1490
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 3
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 24
+- total_eval_batch_size: 6
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 10
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.2735        | 0.05   | 1    | 0.2923          |
+| 0.2852        | 0.25   | 5    | 0.2742          |
+| 0.2007        | 0.5    | 10   | 0.2015          |
+| 0.1742        | 0.75   | 15   | 0.1807          |
+| 0.1854        | 1.0    | 20   | 0.1688          |
+| 0.159         | 1.1125 | 25   | 0.1630          |
+| 0.1444        | 1.3625 | 30   | 0.1592          |
+| 0.1479        | 1.6125 | 35   | 0.1565          |
+| 0.1505        | 1.8625 | 40   | 0.1538          |
+| 0.1369        | 2.1125 | 45   | 0.1518          |
+| 0.1348        | 2.2125 | 50   | 0.1512          |
+| 0.1287        | 2.4625 | 55   | 0.1510          |
+| 0.1359        | 2.7125 | 60   | 0.1498          |
+| 0.1367        | 2.9625 | 65   | 0.1491          |
+| 0.1218        | 3.075  | 70   | 0.1491          |
+| 0.1285        | 3.325  | 75   | 0.1493          |
+| 0.1307        | 3.575  | 80   | 0.1490          |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.41.1
+- Pytorch 2.1.2+cu118
+- Datasets 2.19.1
+- Tokenizers 0.19.1

adapter_model.bin

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