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--- |
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license: apache-2.0 |
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base_model: EleutherAI/pythia-410m |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: pythia410m-taylorswift-2000steps |
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results: [] |
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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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# pythia410m-taylorswift-2000steps |
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This model is a fine-tuned version of [EleutherAI/pythia-410m](https://huggingface.co/EleutherAI/pythia-410m) on [lamini/taylor_swift](https://huggingface.co/datasets/lamini/taylor_swift) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6837 |
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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: 1e-05 |
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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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- distributed_type: tpu |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 4 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 1 |
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- training_steps: 2000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.8241 | 0.61 | 120 | 1.7255 | |
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| 1.0032 | 1.23 | 240 | 1.5268 | |
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| 1.141 | 1.84 | 360 | 1.4654 | |
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| 0.6062 | 2.45 | 480 | 1.4594 | |
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| 0.4412 | 3.07 | 600 | 1.4708 | |
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| 0.4085 | 3.68 | 720 | 1.5156 | |
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| 0.279 | 4.29 | 840 | 1.5411 | |
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| 0.2549 | 4.9 | 960 | 1.5015 | |
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| 0.2972 | 5.52 | 1080 | 1.5476 | |
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| 0.2389 | 6.13 | 1200 | 1.5731 | |
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| 0.2217 | 6.74 | 1320 | 1.5751 | |
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| 0.1253 | 7.36 | 1440 | 1.6184 | |
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| 0.2071 | 7.97 | 1560 | 1.6103 | |
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| 0.2004 | 8.58 | 1680 | 1.6501 | |
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| 0.1017 | 9.2 | 1800 | 1.6778 | |
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| 0.1549 | 9.81 | 1920 | 1.6837 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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