update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- recall
+- precision
+model-index:
+- name: cold_remanandtec_gpu_v1
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# cold_remanandtec_gpu_v1
+
+This model is a fine-tuned version of [ibm/ColD-Fusion](https://huggingface.co/ibm/ColD-Fusion) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0737
+- F1: 0.9462
+- Roc Auc: 0.9592
+- Recall: 0.9362
+- Precision: 0.9565
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Recall | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:------:|:---------:|
+| 0.3606        | 1.0   | 1521 | 0.1974          | 0.8936 | 0.9247  | 0.8936 | 0.8936    |
+| 0.2715        | 2.0   | 3042 | 0.1247          | 0.8989 | 0.9167  | 0.8511 | 0.9524    |
+| 0.1811        | 3.0   | 4563 | 0.0737          | 0.9462 | 0.9592  | 0.9362 | 0.9565    |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.13.1+cu117
+- Datasets 2.8.0
+- Tokenizers 0.13.2