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update model card README.md

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+ ---
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+ license: mit
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: mnli_MULTI
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+ results: []
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+ ---
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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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+
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+ # mnli_MULTI
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+
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+ This model is a fine-tuned version of [WillHeld/roberta-base-mnli](https://huggingface.co/WillHeld/roberta-base-mnli) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5379
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+ - Acc: 0.8407
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Acc |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 0.4798 | 0.17 | 2000 | 0.4797 | 0.8220 |
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+ | 0.4483 | 0.33 | 4000 | 0.4576 | 0.8257 |
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+ | 0.4282 | 0.5 | 6000 | 0.4628 | 0.8298 |
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+ | 0.4333 | 0.67 | 8000 | 0.4426 | 0.8311 |
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+ | 0.4251 | 0.83 | 10000 | 0.4449 | 0.8333 |
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+ | 0.4154 | 1.0 | 12000 | 0.4518 | 0.8376 |
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+ | 0.3064 | 1.17 | 14000 | 0.4845 | 0.8350 |
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+ | 0.3072 | 1.33 | 16000 | 0.4803 | 0.8383 |
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+ | 0.3144 | 1.5 | 18000 | 0.4824 | 0.8322 |
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+ | 0.3025 | 1.66 | 20000 | 0.4634 | 0.8391 |
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+ | 0.3063 | 1.83 | 22000 | 0.4625 | 0.8419 |
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+ | 0.304 | 2.0 | 24000 | 0.4637 | 0.8401 |
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+ | 0.2232 | 2.16 | 26000 | 0.5330 | 0.8434 |
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+ | 0.2215 | 2.33 | 28000 | 0.5338 | 0.8374 |
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+ | 0.2181 | 2.5 | 30000 | 0.5366 | 0.8393 |
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+ | 0.216 | 2.66 | 32000 | 0.5333 | 0.8425 |
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+ | 0.2118 | 2.83 | 34000 | 0.5293 | 0.8414 |
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+ | 0.2128 | 3.0 | 36000 | 0.5379 | 0.8407 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.24.0
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+ - Pytorch 1.13.0+cu117
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+ - Datasets 2.7.1
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+ - Tokenizers 0.12.1