End of training

README.md

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+---
+library_name: peft
+license: llama3.1
+base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: harm-category-labelled-multi-task-16cat-26_12-leaveone-without-animal_env_abuse-llama8b
+  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
+# Configure the base model 
+
+strict: false
+base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
+tokenizer_config: meta-llama/Meta-Llama-3.1-8B-Instruct
+model_type: AutoModelForCausalLM
+
+
+# Output configuration
+hub_model_id: collinear-ai/harm-category-labelled-multi-task-16cat-26_12-leaveone-without-animal_env_abuse-llama8b
+dataset_prepared_path: /workspace/gen_judge/data/collinear-ai/harm-category-labelled-multi-task-16cat-26_12-leaveone-without-animal_env_abuse-llama8b
+output_dir: /workspace/gen_judge/collinear-ai/harm-category-labelled-multi-task-16cat-26_12-leaveone-without-animal_env_abuse-llama8b
+
+# Format the dataset into the right instruction format.
+chat_template: llama3  #llama 3 instruct chat template USE
+datasets:
+  - path: collinear-ai/prompt-response-eval-classification-dataset-final-axolotl
+    split: without_animal_env_abuse_train
+    type: chat_template
+    chat_template: llama3
+    field_messages: train_conv
+    message_field_role: role
+    message_field_content: content
+train_on_inputs: false #FALSE
+
+val_set_size: 0.05
+# Data packing
+sequence_len: 2048
+eval_sample_packing: false
+sample_packing: false
+pad_to_sequence_len: true
+group_by_length: false
+
+# Lora config
+adapter: qlora
+lora_model_dir:
+load_in_8bit: false
+load_in_4bit: true
+lora_r: 64
+lora_alpha: 32
+lora_dropout: 0.1
+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
+lora_modules_to_save: 
+  - embed_tokens
+  - lm_head
+
+# Logging config
+wandb_project: general-judge-harmfulness-bif-data
+wandb_entity: nazneen
+wandb_name: collinear-ai/harm-category-labelled-multi-task-16cat-26_12-leaveone-without-animal_env_abuse-llama8b
+
+# Trainer config
+gradient_accumulation_steps: 2
+micro_batch_size: 12
+num_epochs: 3
+optimizer: paged_adamw_8bit
+lr_scheduler: cosine
+learning_rate: 0.00005
+
+bfloat16: true
+bf16: true
+fp16:
+tf32: false
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 10
+xformers_attention:
+flash_attention: true
+save_safetensors: true
+
+loss_watchdog_threshold: 5.0
+loss_watchdog_patience: 3
+
+warmup_steps: 50
+evals_per_epoch: 3
+eval_table_size:
+eval_max_new_tokens: 500
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.02
+fsdp_config:
+special_tokens:
+  pad_token: "<|end_of_text|>"
+
+
+## weight decay
+## add validation set (split add)
+
+```
+
+</details><br>
+
+# harm-category-labelled-multi-task-16cat-26_12-leaveone-without-animal_env_abuse-llama8b
+
+This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1492
+
+## 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: 5e-05
+- train_batch_size: 12
+- eval_batch_size: 12
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 48
+- total_eval_batch_size: 24
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 50
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| No log        | 0.0007 | 1    | 1.8779          |
+| 0.0152        | 0.3332 | 461  | 0.1341          |
+| 0.0072        | 0.6664 | 922  | 0.1252          |
+| 0.0046        | 0.9996 | 1383 | 0.1301          |
+| 0.0022        | 1.3329 | 1844 | 0.1315          |
+| 0.0028        | 1.6661 | 2305 | 0.1361          |
+| 0.0018        | 1.9993 | 2766 | 0.1338          |
+| 0.0005        | 2.3325 | 3227 | 0.1465          |
+| 0.0003        | 2.6657 | 3688 | 0.1488          |
+| 0.0002        | 2.9989 | 4149 | 0.1492          |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.45.0
+- Pytorch 2.1.2+cu118
+- Datasets 2.19.1
+- Tokenizers 0.20.3