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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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+ metrics:
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+ - f1
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+ - recall
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+ - precision
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+ model-index:
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+ - name: cold_remanandtec_gpu_v1
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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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+ # cold_remanandtec_gpu_v1
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+
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+ This model is a fine-tuned version of [ibm/ColD-Fusion](https://huggingface.co/ibm/ColD-Fusion) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0737
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+ - F1: 0.9462
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+ - Roc Auc: 0.9592
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+ - Recall: 0.9362
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+ - Precision: 0.9565
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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: 2
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+ - eval_batch_size: 2
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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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 3.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Recall | Precision |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:------:|:---------:|
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+ | 0.3606 | 1.0 | 1521 | 0.1974 | 0.8936 | 0.9247 | 0.8936 | 0.8936 |
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+ | 0.2715 | 2.0 | 3042 | 0.1247 | 0.8989 | 0.9167 | 0.8511 | 0.9524 |
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+ | 0.1811 | 3.0 | 4563 | 0.0737 | 0.9462 | 0.9592 | 0.9362 | 0.9565 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.25.1
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+ - Pytorch 1.13.1+cu117
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+ - Datasets 2.8.0
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+ - Tokenizers 0.13.2