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esm2_t6_8M_UR50D-Ab-CLIP-v0
arjan-hada/esm2_t6_8M_UR50D-Ab-CLIP-v0
esm2_t6_8M_UR50D-Ab-CLIP-v0 is a machine learning model from arjan-hada. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- esm
- Access
- Public
- Created
- Jul 8, 2024
- Updated
- Jul 9, 2024
- SHA
- 267eeb50
Base models
Model card
From the Hugging Face model README
<!-- 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 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
- Library
- transformers
- Type
- esm
- License
- mit
- Created
- Jul 8, 2024
- Updated
- Jul 9, 2024