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---
tags:
- generated_from_trainer
model-index:
- name: TCS_Pair
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. -->
# TCS_Pair
This model is a fine-tuned version of [mgh6/esm_cluster_35M_linear](https://huggingface.co/mgh6/esm_cluster_35M_linear) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1515
## 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: 0.001
- train_batch_size: 80
- eval_batch_size: 80
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1694 | 0.13 | 100 | 0.1876 |
| 0.1104 | 0.27 | 200 | 0.1856 |
| 0.0976 | 0.4 | 300 | 0.2082 |
| 0.0858 | 0.54 | 400 | 0.1908 |
| 0.0832 | 0.67 | 500 | 0.1575 |
| 0.0853 | 0.81 | 600 | 0.1549 |
| 0.0788 | 0.94 | 700 | 0.1598 |
| 0.0629 | 1.07 | 800 | 0.1386 |
| 0.0579 | 1.21 | 900 | 0.2071 |
| 0.0571 | 1.34 | 1000 | 0.1667 |
| 0.0567 | 1.48 | 1100 | 0.1421 |
| 0.0527 | 1.61 | 1200 | 0.1623 |
| 0.0553 | 1.74 | 1300 | 0.1827 |
| 0.0557 | 1.88 | 1400 | 0.1535 |
| 0.0523 | 2.01 | 1500 | 0.1353 |
| 0.0358 | 2.15 | 1600 | 0.1409 |
| 0.041 | 2.28 | 1700 | 0.1502 |
| 0.042 | 2.42 | 1800 | 0.1427 |
| 0.04 | 2.55 | 1900 | 0.1505 |
| 0.04 | 2.68 | 2000 | 0.1366 |
| 0.0392 | 2.82 | 2100 | 0.1236 |
| 0.0409 | 2.95 | 2200 | 0.1210 |
| 0.0327 | 3.09 | 2300 | 0.1448 |
| 0.0293 | 3.22 | 2400 | 0.1535 |
| 0.0265 | 3.36 | 2500 | 0.1529 |
| 0.0268 | 3.49 | 2600 | 0.1557 |
| 0.0241 | 3.62 | 2700 | 0.1505 |
| 0.0264 | 3.76 | 2800 | 0.1447 |
| 0.0286 | 3.89 | 2900 | 0.1442 |
| 0.0306 | 4.03 | 3000 | 0.1504 |
| 0.0152 | 4.16 | 3100 | 0.1311 |
| 0.0185 | 4.3 | 3200 | 0.1873 |
| 0.0212 | 4.43 | 3300 | 0.1396 |
| 0.022 | 4.56 | 3400 | 0.1663 |
| 0.0206 | 4.7 | 3500 | 0.1443 |
| 0.0231 | 4.83 | 3600 | 0.1483 |
| 0.0172 | 4.97 | 3700 | 0.1413 |
| 0.0134 | 5.1 | 3800 | 0.1472 |
| 0.0129 | 5.23 | 3900 | 0.1442 |
| 0.0126 | 5.37 | 4000 | 0.1369 |
| 0.013 | 5.5 | 4100 | 0.1576 |
| 0.012 | 5.64 | 4200 | 0.1348 |
| 0.013 | 5.77 | 4300 | 0.1572 |
| 0.0123 | 5.91 | 4400 | 0.1529 |
| 0.0099 | 6.04 | 4500 | 0.1425 |
| 0.0072 | 6.17 | 4600 | 0.1540 |
| 0.0081 | 6.31 | 4700 | 0.1463 |
| 0.0075 | 6.44 | 4800 | 0.1540 |
| 0.0078 | 6.58 | 4900 | 0.1418 |
| 0.0062 | 6.71 | 5000 | 0.1640 |
| 0.0062 | 6.85 | 5100 | 0.1392 |
| 0.0068 | 6.98 | 5200 | 0.1572 |
| 0.0054 | 7.11 | 5300 | 0.1485 |
| 0.0046 | 7.25 | 5400 | 0.1445 |
| 0.0054 | 7.38 | 5500 | 0.1488 |
| 0.0033 | 7.52 | 5600 | 0.1478 |
| 0.0041 | 7.65 | 5700 | 0.1514 |
| 0.0044 | 7.79 | 5800 | 0.1508 |
| 0.0025 | 7.92 | 5900 | 0.1515 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
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