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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-XYZCompany-1000-steps |
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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-XYZCompany-1000-steps |
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This model is a fine-tuned version of [EleutherAI/pythia-410m](https://huggingface.co/EleutherAI/pythia-410m) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2944 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.2939 | 0.32 | 50 | 0.2774 | |
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| 0.2993 | 0.63 | 100 | 0.2531 | |
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| 0.2538 | 0.95 | 150 | 0.2429 | |
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| 0.1829 | 1.27 | 200 | 0.2393 | |
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| 0.187 | 1.59 | 250 | 0.2326 | |
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| 0.1737 | 1.9 | 300 | 0.2308 | |
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| 0.1195 | 2.22 | 350 | 0.2405 | |
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| 0.1263 | 2.54 | 400 | 0.2392 | |
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| 0.1248 | 2.86 | 450 | 0.2374 | |
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| 0.069 | 3.17 | 500 | 0.2545 | |
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| 0.08 | 3.49 | 550 | 0.2530 | |
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| 0.0763 | 3.81 | 600 | 0.2553 | |
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| 0.0532 | 4.13 | 650 | 0.2690 | |
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| 0.0465 | 4.44 | 700 | 0.2727 | |
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| 0.0538 | 4.76 | 750 | 0.2734 | |
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| 0.037 | 5.08 | 800 | 0.2834 | |
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| 0.0334 | 5.4 | 850 | 0.2859 | |
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| 0.0299 | 5.71 | 900 | 0.2872 | |
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| 0.0318 | 6.03 | 950 | 0.2906 | |
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| 0.0256 | 6.35 | 1000 | 0.2944 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.17.1 |
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- Tokenizers 0.13.2 |
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