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--- |
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license: apache-2.0 |
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base_model: google/long-t5-tglobal-xl |
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tags: |
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- generated_from_trainer |
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datasets: |
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- learn3r/summ_screen_fd_bp |
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model-index: |
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- name: longt5_xl_sfd_bp_10 |
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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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# longt5_xl_sfd_bp_10 |
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This model is a fine-tuned version of [google/long-t5-tglobal-xl](https://huggingface.co/google/long-t5-tglobal-xl) on the learn3r/summ_screen_fd_bp dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.8921 |
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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: 0.001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 256 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- num_epochs: 20.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.3973 | 0.97 | 14 | 1.9027 | |
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| 1.9188 | 1.95 | 28 | 1.6941 | |
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| 1.4297 | 2.99 | 43 | 1.5011 | |
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| 1.2759 | 3.97 | 57 | 1.5048 | |
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| 1.1421 | 4.94 | 71 | 1.5463 | |
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| 0.9605 | 5.98 | 86 | 1.6270 | |
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| 0.8082 | 6.96 | 100 | 1.7646 | |
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| 0.664 | 8.0 | 115 | 1.7878 | |
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| 0.5471 | 8.97 | 129 | 1.9500 | |
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| 0.4349 | 9.95 | 143 | 1.9657 | |
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| 0.4338 | 10.99 | 158 | 2.1351 | |
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| 0.2887 | 11.97 | 172 | 2.1166 | |
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| 0.2753 | 12.94 | 186 | 2.4357 | |
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| 0.2114 | 13.98 | 201 | 2.5789 | |
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| 0.1805 | 14.96 | 215 | 2.6075 | |
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| 0.1543 | 16.0 | 230 | 2.5597 | |
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| 0.5166 | 16.97 | 244 | 2.5067 | |
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| 0.1117 | 17.95 | 258 | 2.8087 | |
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| 0.0895 | 18.99 | 273 | 2.7578 | |
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| 0.0779 | 19.48 | 280 | 2.8921 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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