austindavis
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README.md
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###
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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## Model Card Authors [optional]
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## Model Card Contact
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[More Information Needed]
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---
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base_model: austindavis/gpt2-lichess-uci-2016-01_11
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tags:
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- generated_from_trainer
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model-index:
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- name: gpt2-lichess-uci-202306
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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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# gpt2-lichess-uci-202306
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This model is a fine-tuned version of [austindavis/gpt2-lichess-uci-2016-01_11](https://huggingface.co/austindavis/gpt2-lichess-uci-2016-01_11) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8839
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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: 0.002
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- train_batch_size: 20
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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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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| 1.022 | 0.1323 | 165000 | 1.0013 |
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| 1.0204 | 0.1443 | 180000 | 1.0001 |
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| 1.0186 | 0.1563 | 195000 | 0.9973 |
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| 1.0155 | 0.1684 | 210000 | 0.9954 |
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| 1.0133 | 0.1804 | 225000 | 0.9935 |
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| 1.0118 | 0.1924 | 240000 | 0.9924 |
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| 1.0092 | 0.2044 | 255000 | 0.9893 |
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| 1.007 | 0.2165 | 270000 | 0.9881 |
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| 1.0057 | 0.2285 | 285000 | 0.9868 |
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| 1.0035 | 0.2405 | 300000 | 0.9879 |
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| 1.004 | 0.2525 | 315000 | 0.9843 |
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| 1.0005 | 0.2646 | 330000 | 0.9807 |
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| 0.9986 | 0.2766 | 345000 | 0.9805 |
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| 0.9983 | 0.2886 | 360000 | 0.9776 |
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| 0.9965 | 0.3006 | 375000 | 0.9781 |
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| 0.9935 | 0.3127 | 390000 | 0.9754 |
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| 0.9935 | 0.3247 | 405000 | 0.9761 |
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| 0.9916 | 0.3367 | 420000 | 0.9743 |
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| 0.989 | 0.3487 | 435000 | 0.9712 |
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| 0.988 | 0.3608 | 450000 | 0.9702 |
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| 0.9862 | 0.3728 | 465000 | 0.9703 |
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| 0.9837 | 0.3848 | 480000 | 0.9680 |
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| 0.983 | 0.3968 | 495000 | 0.9643 |
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| 0.9816 | 0.4089 | 510000 | 0.9634 |
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| 0.9796 | 0.4209 | 525000 | 0.9628 |
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| 0.9777 | 0.4329 | 540000 | 0.9612 |
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| 0.9744 | 0.4449 | 555000 | 0.9587 |
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| 0.9733 | 0.4570 | 570000 | 0.9590 |
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| 0.97 | 0.4690 | 585000 | 0.9566 |
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| 0.9693 | 0.4810 | 600000 | 0.9539 |
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| 0.9684 | 0.4930 | 615000 | 0.9532 |
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| 0.9652 | 0.5051 | 630000 | 0.9509 |
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| 0.9644 | 0.5171 | 645000 | 0.9501 |
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| 0.9614 | 0.5291 | 660000 | 0.9479 |
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| 0.9606 | 0.5411 | 675000 | 0.9466 |
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| 0.9597 | 0.5532 | 690000 | 0.9444 |
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| 0.9556 | 0.5652 | 705000 | 0.9416 |
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| 0.9541 | 0.5772 | 720000 | 0.9413 |
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| 0.9522 | 0.5892 | 735000 | 0.9382 |
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| 0.9491 | 0.6013 | 750000 | 0.9367 |
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| 0.9471 | 0.6133 | 765000 | 0.9354 |
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| 0.9459 | 0.6253 | 780000 | 0.9321 |
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| 0.9416 | 0.6373 | 795000 | 0.9309 |
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| 0.9401 | 0.6494 | 810000 | 0.9287 |
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| 0.9383 | 0.6614 | 825000 | 0.9265 |
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| 0.9375 | 0.6734 | 840000 | 0.9238 |
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| 0.9354 | 0.6854 | 855000 | 0.9225 |
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| 0.9323 | 0.6975 | 870000 | 0.9196 |
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| 0.9291 | 0.7095 | 885000 | 0.9189 |
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| 0.9276 | 0.7215 | 900000 | 0.9165 |
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| 0.9266 | 0.7335 | 915000 | 0.9142 |
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| 0.9221 | 0.7456 | 930000 | 0.9130 |
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| 0.9216 | 0.7576 | 945000 | 0.9106 |
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| 0.9191 | 0.7696 | 960000 | 0.9084 |
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| 0.9152 | 0.7816 | 975000 | 0.9062 |
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| 0.9127 | 0.7937 | 990000 | 0.9039 |
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| 0.9133 | 0.8057 | 1005000 | 0.9014 |
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| 0.9086 | 0.8177 | 1020000 | 0.8997 |
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| 0.9078 | 0.8297 | 1035000 | 0.8978 |
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| 0.9054 | 0.8418 | 1050000 | 0.8955 |
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| 0.9037 | 0.8538 | 1065000 | 0.8943 |
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| 0.9015 | 0.8658 | 1080000 | 0.8926 |
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| 0.9006 | 0.8778 | 1095000 | 0.8912 |
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| 0.8991 | 0.8899 | 1110000 | 0.8897 |
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| 0.897 | 0.9019 | 1125000 | 0.8885 |
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| 0.8971 | 0.9139 | 1140000 | 0.8873 |
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| 0.894 | 0.9259 | 1155000 | 0.8864 |
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| 0.8938 | 0.9380 | 1170000 | 0.8854 |
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| 0.893 | 0.9500 | 1185000 | 0.8848 |
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| 0.8922 | 0.9620 | 1200000 | 0.8844 |
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| 0.8936 | 0.9740 | 1215000 | 0.8841 |
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| 0.8923 | 0.9861 | 1230000 | 0.8840 |
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| 0.8922 | 0.9981 | 1245000 | 0.8839 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.3.0
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 102086376
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version https://git-lfs.github.com/spec/v1
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oid sha256:12ce7e4f8c5ca4c632850af3d296fe8a118132f199f2853b0b7484336d6f97ff
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size 102086376
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