---
license: mit
base_model: facebook/esm2_t6_8M_UR50D
tags:
- generated_from_trainer
model-index:
- name: esm2_t6_8M_UR50D-Ab-CLIP-v0
  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_t6_8M_UR50D-Ab-CLIP-v0

This model is a fine-tuned version of [facebook/esm2_t6_8M_UR50D](https://huggingface.co/facebook/esm2_t6_8M_UR50D) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8743
- Alignment: 1.0213
- Uniformity: -3.0773
- Contrastive Accuracy: 0.2267
- Top 3 Accuracy: 0.5067

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 5
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Alignment | Uniformity | Contrastive Accuracy | Top 3 Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:----------:|:--------------------:|:--------------:|
| 1.0153        | 1.0   | 196  | 1.2958          | 1.2729    | -2.4114    | 0.0680               | 0.1837         |
| 0.4623        | 2.0   | 392  | 1.0729          | 1.1755    | -2.8008    | 0.0952               | 0.2653         |
| 0.2646        | 3.0   | 588  | 1.0867          | 1.1511    | -2.9630    | 0.1361               | 0.3265         |
| 0.1815        | 4.0   | 784  | 1.0768          | 1.1490    | -3.0403    | 0.1293               | 0.3673         |
| 0.1403        | 5.0   | 980  | 1.0527          | 1.1426    | -3.0663    | 0.1224               | 0.3605         |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1