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End of training
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README.md
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---
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license: apache-2.0
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base_model: bert-base-uncased
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tags:
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- generated_from_trainer
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datasets:
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- glue
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metrics:
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- accuracy
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model-index:
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- name: bert-base-uncased-rte-ia3-epochs-10-lr-0.005
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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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# bert-base-uncased-rte-ia3-epochs-10-lr-0.005
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6986
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- Accuracy: 0.7
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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: 0.005
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 28
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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_ratio: 0.06
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 75 | 0.6797 | 0.58 |
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| No log | 2.0 | 150 | 0.6631 | 0.61 |
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| No log | 3.0 | 225 | 0.6239 | 0.62 |
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| No log | 4.0 | 300 | 0.5983 | 0.63 |
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| No log | 5.0 | 375 | 0.6250 | 0.68 |
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| No log | 6.0 | 450 | 0.6487 | 0.67 |
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| 0.6417 | 7.0 | 525 | 0.6473 | 0.64 |
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| 0.6417 | 8.0 | 600 | 0.6558 | 0.68 |
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| 0.6417 | 9.0 | 675 | 0.6865 | 0.69 |
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| 0.6417 | 10.0 | 750 | 0.6986 | 0.7 |
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### Framework versions
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- Transformers 4.32.0.dev0
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- Pytorch 2.0.1
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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