End of training
Browse files- README.md +64 -63
- adapter_model.safetensors +2 -2
- config.json +1 -1
- pytorch_model.bin +1 -1
README.md
CHANGED
@@ -69,7 +69,7 @@ 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.
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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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@@ -84,7 +84,7 @@ 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:
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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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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:
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.
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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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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:-----:|:---------------:|
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| 25.9906 | 0.0001 | 1 | 29.
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### Framework versions
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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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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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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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### 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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| 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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### Framework versions
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adapter_model.safetensors
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size
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size 48
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config.json
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"rotary_emb_base": 10000,
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"rotary_pct": 0.25,
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"tie_word_embeddings": false,
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"torch_dtype": "
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"transformers_version": "4.41.2",
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"use_cache": false,
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"use_parallel_residual": true,
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"rotary_emb_base": 10000,
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"rotary_pct": 0.25,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.41.2",
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"use_cache": false,
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"use_parallel_residual": true,
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pytorch_model.bin
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size 324696090
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