mhr2004/roberta-large-nsp-1000-1e-06-8
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- model.safetensors +1 -1
- training_args.bin +1 -1
README.md
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@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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## Model description
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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: linear
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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| No log | 1.0 | 32 | 0.
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| No log | 2.0 | 64 | 0.
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| No log | 3.0 | 96 | 0.
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| No log | 4.0 | 128 | 0.
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| No log | 5.0 | 160 | 0.
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| No log | 6.0 | 192 | 0.
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| 0.6429 | 17.0 | 544 | 0.5719 |
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| 0.6429 | 18.0 | 576 | 0.5615 |
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| 0.5906 | 19.0 | 608 | 0.5588 |
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| 0.5906 | 20.0 | 640 | 0.5575 |
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| 0.5906 | 21.0 | 672 | 0.5561 |
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| 0.5906 | 22.0 | 704 | 0.5516 |
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| 0.5906 | 23.0 | 736 | 0.5499 |
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| 0.5906 | 24.0 | 768 | 0.5499 |
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| 0.5684 | 25.0 | 800 | 0.5494 |
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### Framework versions
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5884
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## Model description
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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: linear
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- num_epochs: 30
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| No log | 1.0 | 32 | 0.6935 |
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| No log | 2.0 | 64 | 0.6888 |
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| No log | 3.0 | 96 | 0.6834 |
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| No log | 4.0 | 128 | 0.6600 |
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| No log | 5.0 | 160 | 0.6272 |
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| No log | 6.0 | 192 | 0.6098 |
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| 0.6812 | 7.0 | 224 | 0.5968 |
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| 0.6812 | 8.0 | 256 | 0.5925 |
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| 0.6812 | 9.0 | 288 | 0.5899 |
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| 0.6812 | 10.0 | 320 | 0.5873 |
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| 0.6812 | 11.0 | 352 | 0.5866 |
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| 0.6812 | 12.0 | 384 | 0.5870 |
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| 0.6056 | 13.0 | 416 | 0.5884 |
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| 0.6056 | 14.0 | 448 | 0.5889 |
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| 0.6056 | 15.0 | 480 | 0.5887 |
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| 0.6056 | 16.0 | 512 | 0.5884 |
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### Framework versions
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model.safetensors
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training_args.bin
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