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---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: facebook/esm2_t30_150M_UR50D
metrics:
- accuracy
model-index:
- name: esm2_t130_150M-lora-classifier_2024-04-26_10-08-51
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_t130_150M-lora-classifier_2024-04-26_10-08-51
This model is a fine-tuned version of [facebook/esm2_t30_150M_UR50D](https://huggingface.co./facebook/esm2_t30_150M_UR50D) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4537
- Accuracy: 0.8984
## 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: 0.0008701568055793088
- train_batch_size: 28
- eval_batch_size: 28
- seed: 8893
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6764 | 1.0 | 55 | 0.6794 | 0.5820 |
| 0.5521 | 2.0 | 110 | 0.6192 | 0.6777 |
| 0.5409 | 3.0 | 165 | 0.5147 | 0.7383 |
| 0.5518 | 4.0 | 220 | 0.3518 | 0.8672 |
| 0.1386 | 5.0 | 275 | 0.3596 | 0.8574 |
| 0.303 | 6.0 | 330 | 0.4030 | 0.8359 |
| 0.1962 | 7.0 | 385 | 0.3143 | 0.8848 |
| 0.1501 | 8.0 | 440 | 0.3232 | 0.8652 |
| 0.2994 | 9.0 | 495 | 0.3014 | 0.8770 |
| 0.0914 | 10.0 | 550 | 0.2980 | 0.8887 |
| 0.2108 | 11.0 | 605 | 0.2854 | 0.8770 |
| 0.2896 | 12.0 | 660 | 0.3684 | 0.8691 |
| 0.0818 | 13.0 | 715 | 0.3349 | 0.8828 |
| 0.3152 | 14.0 | 770 | 0.3530 | 0.8848 |
| 0.0554 | 15.0 | 825 | 0.3371 | 0.8887 |
| 0.1928 | 16.0 | 880 | 0.3347 | 0.875 |
| 0.2658 | 17.0 | 935 | 0.3765 | 0.8867 |
| 0.4242 | 18.0 | 990 | 0.4166 | 0.8945 |
| 0.0964 | 19.0 | 1045 | 0.3400 | 0.8945 |
| 0.0375 | 20.0 | 1100 | 0.3581 | 0.9004 |
| 0.1781 | 21.0 | 1155 | 0.3816 | 0.8848 |
| 0.1563 | 22.0 | 1210 | 0.3940 | 0.8867 |
| 0.017 | 23.0 | 1265 | 0.4098 | 0.8926 |
| 0.1866 | 24.0 | 1320 | 0.4710 | 0.8770 |
| 0.0632 | 25.0 | 1375 | 0.4541 | 0.8828 |
| 0.1501 | 26.0 | 1430 | 0.4645 | 0.8828 |
| 0.109 | 27.0 | 1485 | 0.4434 | 0.8926 |
| 0.0353 | 28.0 | 1540 | 0.4264 | 0.8984 |
| 0.4502 | 29.0 | 1595 | 0.4479 | 0.8984 |
| 0.0341 | 30.0 | 1650 | 0.4537 | 0.8984 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.16.1
- Tokenizers 0.15.2 |