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--- |
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base_model: EleutherAI/pythia-160m-deduped |
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library_name: transformers |
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license: apache-2.0 |
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tags: |
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- axolotl |
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- relora |
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- generated_from_trainer |
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model-index: |
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- name: pythia-160m-dolphin-extended |
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results: [] |
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datasets: |
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- cognitivecomputations/dolphin |
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- llamafactory/alpaca_gpt4_en |
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language: |
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- en |
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metrics: |
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- accuracy |
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- bleu |
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- rouge |
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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/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) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.1` |
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```yaml |
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base_model: EleutherAI/pythia-160m-deduped |
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load_in_8bit: |
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datasets: |
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- path: vicgalle/alpaca-gpt4 |
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type: alpaca |
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- path: llamafactory/alpaca_gpt4_en |
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type: alpaca |
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- path: cognitivecomputations/dolphin |
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name: flan1m-alpaca-uncensored |
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type: alpaca |
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shards: 10 |
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dataset_prepared_path: ds-mega-alpaca |
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#dataset_shard_num: 10 |
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chat_template: inst |
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val_set_size: 0.001 |
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adapter: lora |
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lora_model_dir: |
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sequence_len: 2048 |
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lora_r: 16 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_target_modules: |
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- query_key_value |
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lora_target_linear: |
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lora_fan_in_fan_out: true # pythia/GPTNeoX lora specific |
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lora_modules_to_save: |
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- embed_in |
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- embed_out |
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- lm_head |
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lora_on_cpu: false |
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# ReLoRA configuration |
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# # Must use either 'lora' or 'qlora' adapter, and does not support fsdp or deepspeed |
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# relora_steps: # Number of steps per ReLoRA restart |
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# relora_warmup_steps: # Number of per-restart warmup steps |
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# relora_anneal_steps: # Number of anneal steps for each relora cycle |
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# relora_prune_ratio: # threshold for optimizer magnitude when pruning |
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# relora_cpu_offload: # True to perform lora weight merges on cpu during restarts, for modest gpu memory savings |
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relora_steps: 600 |
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relora_warmup_steps: 10 |
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relora_cpu_offload: true |
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wandb_project: pythia |
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wandb_entity: |
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wandb_watch: |
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wandb_name: pythia-160m-dolphin-extended |
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wandb_log_model: |
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output_dir: ./outputs/lora-alpaca-pythia-160m-dolphin-extended |
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gradient_accumulation_steps: 16 |
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micro_batch_size: 1 |
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num_epochs: 1 |
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learning_rate: 0.0004 |
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lr_scheduler: cosine_with_restarts |
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#cosine_min_lr_ratio: 0.1 |
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train_on_inputs: false |
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group_by_length: false |
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#bf16: auto |
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#fp16: true |
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#tf32: false |
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float16: true |
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flash_attn: |
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xformers_attention: true |
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optimizer: paged_adamw_8bit |
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gpu_memory_limit: 8GiB |
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hub_model_id: jtatman/pythia-160m-dolphin-extended |
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early_stopping_patience: 10 |
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#resume_from_checkpoint: outputs/lora-alpaca-pythia-160m-dolphin-extended/checkpoint-11400 |
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auto_resume_from_checkpoints: true |
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local_rank: |
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weight_decay: 0.0 |
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#evals_per_epoch: 4 |
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eval_steps: 200 |
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logging_steps: 1 |
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save_steps: 200 |
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save_total_limit: 5 |
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warmup_steps: 100 |
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tokens: |
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- "[INST]" |
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- "[/INST]" |
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``` |
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</details><br> |
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# pythia-160m-dolphin-extended |
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This model is a fine-tuned version of [EleutherAI/pythia-160m-deduped](https://huggingface.co/EleutherAI/pythia-160m-deduped) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 6.6729 |
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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: 0.0004 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 25.9906 | 0.0001 | 1 | 29.5342 | |
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| 21.1303 | 0.0167 | 200 | 20.2350 | |
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| 16.5026 | 0.0334 | 400 | 18.4930 | |
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| 17.2725 | 0.0500 | 600 | 16.3395 | |
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| 11.9697 | 0.0667 | 800 | 12.1401 | |
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| 11.3783 | 0.0834 | 1000 | 11.8383 | |
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| 12.8084 | 0.1001 | 1200 | 12.9667 | |
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| 9.4119 | 0.1167 | 1400 | 9.8787 | |
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| 10.3527 | 0.1334 | 1600 | 10.0560 | |
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| 9.3545 | 0.1501 | 1800 | 9.7355 | |
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| 8.9165 | 0.1668 | 2000 | 9.1513 | |
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| 8.5467 | 0.1835 | 2200 | 8.2025 | |
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| 7.9152 | 0.2001 | 2400 | 7.6616 | |
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| 7.3362 | 0.2168 | 2600 | 7.5699 | |
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| 7.9374 | 0.2335 | 2800 | 7.4818 | |
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| 7.838 | 0.2502 | 3000 | 7.4635 | |
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| 7.5731 | 0.2668 | 3200 | 7.4899 | |
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| 7.8289 | 0.2835 | 3400 | 7.3594 | |
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| 7.8906 | 0.3002 | 3600 | 8.0934 | |
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| 7.7318 | 0.3169 | 3800 | 7.5812 | |
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| 7.2089 | 0.3335 | 4000 | 7.4839 | |
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| 7.202 | 0.3502 | 4200 | 7.4486 | |
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| 6.9493 | 0.3669 | 4400 | 7.3208 | |
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| 7.1492 | 0.3836 | 4600 | 7.2469 | |
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| 7.3443 | 0.4003 | 4800 | 7.1378 | |
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| 7.7056 | 0.4169 | 5000 | 7.1385 | |
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| 55.0553 | 0.4336 | 5200 | 50.0135 | |
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| 7.1868 | 0.4503 | 5400 | 6.9898 | |
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| 6.5803 | 0.4670 | 5600 | 6.9559 | |
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| 8.6171 | 0.4836 | 5800 | 7.9075 | |
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| 7.1373 | 0.5003 | 6000 | 6.9280 | |
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| 6.7077 | 0.5170 | 6200 | 6.8797 | |
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| 7.0026 | 0.5337 | 6400 | 6.8635 | |
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| 6.6797 | 0.5504 | 6600 | 6.8178 | |
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| 6.8067 | 0.5670 | 6800 | 6.7893 | |
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| 6.5979 | 0.5837 | 7000 | 6.8106 | |
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| 6.7283 | 0.6004 | 7200 | 6.7998 | |
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| 7.0015 | 0.6171 | 7400 | 6.7705 | |
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| 6.1182 | 0.6337 | 7600 | 6.7592 | |
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| 6.7919 | 0.6504 | 7800 | 6.7446 | |
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| 6.4523 | 0.6671 | 8000 | 6.7260 | |
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| 6.765 | 0.6838 | 8200 | 6.7135 | |
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| 6.4625 | 0.7004 | 8400 | 6.7099 | |
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| 6.79 | 0.7171 | 8600 | 6.7070 | |
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| 6.6101 | 0.7338 | 8800 | 6.7017 | |
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| 6.7541 | 0.7505 | 9000 | 6.6964 | |
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| 6.7777 | 0.7672 | 9200 | 6.6901 | |
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| 7.2082 | 0.7838 | 9400 | 6.6869 | |
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| 6.4263 | 0.8005 | 9600 | 6.6875 | |
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| 6.1944 | 0.8172 | 9800 | 6.6803 | |
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| 6.7745 | 0.8339 | 10000 | 6.6865 | |
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| 6.6746 | 0.8505 | 10200 | 6.6756 | |
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| 6.6319 | 0.8672 | 10400 | 6.6941 | |
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| 6.6657 | 0.8839 | 10600 | 6.6764 | |
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| 6.8516 | 0.9006 | 10800 | 6.6776 | |
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| 6.6391 | 0.9173 | 11000 | 6.6749 | |
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| 6.5763 | 0.9339 | 11200 | 6.6729 | |
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| 6.585 | 0.9506 | 11400 | 6.6694 | |
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| 6.2999 | 0.9673 | 11600 | 6.6722 | |
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| 6.8343 | 0.9840 | 11800 | 6.6729 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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### Evaluation Results |
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| Groups |Version| Filter |n-shot| Metric | Value | |Stderr| |
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|--------------------|-------|----------------|-----:|-----------|------:|---|-----:| |
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|Open LLM Leaderboard|N/A |none | 5|rouge2_max |16.4873|± |1.0172| |
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| - winogrande | 1|none | 5|acc | 0.5120|± |0.0224| |
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| - gsm8k | 3|strict-match | 5|exact_match| 0.0060|± |0.0035| |
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| - hellaswag | 1|none | 10|acc | 0.3520|± |0.0214| |
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| - mmlu |N/A |none | 0|acc | 0.2533|± |0.0039| |
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| | |none | 5|rouge2_acc | 0.1920|± |0.0176| |
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| | |none | 5|rougeL_acc | 0.3860|± |0.0218| |
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| | |flexible-extract| 5|exact_match| 0.0220|± |0.0066| |
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| | |strict-match | 5|exact_match| 0.0060|± |0.0035| |
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| | |none | 5|rougeL_diff|-0.7765|± |1.0034| |
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| | |none | 5|rouge1_acc | 0.3700|± |0.0216| |
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| | |none | 5|rouge1_diff|-1.5564|± |1.0223| |
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| | |none | 5|acc_norm | 0.3180|± |0.0145| |
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| | |none | 5|bleu_diff |-0.6500|± |0.6421| |
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| | |none | 5|rouge1_max |36.3550|± |0.9462| |
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| | |none | 5|acc | 0.2664|± |0.0036| |
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| | |none | 5|rougeL_max |33.8798|± |0.9367| |
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| | |none | 5|bleu_max |15.2292|± |0.6714| |
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| | |none | 5|bleu_acc | 0.4360|± |0.0222| |
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| | |none | 5|rouge2_diff|-3.3178|± |0.9477| |
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| - mmlu |N/A |none | 0|acc | 0.2533|± |0.0039| |
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| - humanities |N/A |none | 5|acc | 0.2408|± |0.0075| |
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| - other |N/A |none | 5|acc | 0.2443|± |0.0080| |
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| - social_sciences |N/A |none | 5|acc | 0.2538|± |0.0081| |
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| - stem |N/A |none | 5|acc | 0.2740|± |0.0079| |
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| - truthfulqa |N/A |none | 0|rouge2_max |16.4873|± |1.0172| |
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| | |none | 0|rouge2_acc | 0.1920|± |0.0176| |
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| | |none | 0|rougeL_acc | 0.3860|± |0.0218| |
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| | |none | 0|rougeL_diff|-0.7765|± |1.0034| |
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| | |none | 0|rouge1_acc | 0.3700|± |0.0216| |
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| | |none | 0|rouge1_diff|-1.5564|± |1.0223| |
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| | |none | 0|bleu_diff |-0.6500|± |0.6421| |
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| | |none | 0|rouge1_max |36.3550|± |0.9462| |
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| | |none | 0|acc | 0.3435|± |0.0137| |
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| | |none | 0|rougeL_max |33.8798|± |0.9367| |
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| | |none | 0|bleu_max |15.2292|± |0.6714| |
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| | |none | 0|bleu_acc | 0.4360|± |0.0222| |
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| | |none | 0|rouge2_diff|-3.3178|± |0.9477| |
