Model save

README.md

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+---
+license: mit
+base_model: facebook/esm2_t33_650M_UR50D
+tags:
+- generated_from_trainer
+metrics:
+- spearmanr
+model-index:
+- name: esm2_t33_650M_UR50D-finetuned-Ab14H-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. -->
+
+# esm2_t33_650M_UR50D-finetuned-Ab14H-v1
+
+This model is a fine-tuned version of [facebook/esm2_t33_650M_UR50D](https://huggingface.co/facebook/esm2_t33_650M_UR50D) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2626
+- Spearmanr: 0.6109
+
+## 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: 32
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Spearmanr |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|
+| 3.7775        | 1.0   | 643  | 1.8108          | 0.5994    |
+| 1.4213        | 2.0   | 1286 | 1.3513          | 0.6542    |
+| 1.2606        | 3.0   | 1929 | 1.1680          | 0.6526    |
+| 1.1149        | 4.0   | 2572 | 1.3710          | 0.6268    |
+| 1.0178        | 5.0   | 3215 | 1.2131          | 0.6613    |
+| 0.9379        | 6.0   | 3858 | 1.2329          | 0.6349    |
+| 0.6642        | 7.0   | 4501 | 1.1996          | 0.6333    |
+| 0.5235        | 8.0   | 5144 | 1.2297          | 0.6190    |
+| 0.4256        | 9.0   | 5787 | 1.2410          | 0.6175    |
+| 0.3714        | 10.0  | 6430 | 1.2626          | 0.6109    |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

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