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---
license: mit
tags:
- generated_from_trainer
model-index:
- name: roberta-base-mnli_CollSgE
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. -->
# roberta-base-mnli_CollSgE
This model is a fine-tuned version of [WillHeld/roberta-base-mnli](https://huggingface.co/WillHeld/roberta-base-mnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7610
- Acc: 0.8445
## 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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Acc |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.4123 | 0.17 | 2000 | 0.4693 | 0.8332 |
| 0.4028 | 0.33 | 4000 | 0.4624 | 0.8338 |
| 0.3888 | 0.5 | 6000 | 0.4500 | 0.8375 |
| 0.3841 | 0.67 | 8000 | 0.4281 | 0.8416 |
| 0.3783 | 0.83 | 10000 | 0.4434 | 0.8365 |
| 0.3759 | 1.0 | 12000 | 0.4400 | 0.8418 |
| 0.2721 | 1.17 | 14000 | 0.5022 | 0.8427 |
| 0.2736 | 1.33 | 16000 | 0.5252 | 0.8431 |
| 0.2821 | 1.5 | 18000 | 0.4887 | 0.8409 |
| 0.2802 | 1.67 | 20000 | 0.4758 | 0.8458 |
| 0.2794 | 1.83 | 22000 | 0.4611 | 0.8458 |
| 0.2797 | 2.0 | 24000 | 0.4936 | 0.8456 |
| 0.1915 | 2.17 | 26000 | 0.5545 | 0.8462 |
| 0.1946 | 2.33 | 28000 | 0.5731 | 0.8443 |
| 0.2007 | 2.5 | 30000 | 0.5507 | 0.8428 |
| 0.2008 | 2.67 | 32000 | 0.5499 | 0.8454 |
| 0.1971 | 2.84 | 34000 | 0.5274 | 0.8483 |
| 0.2054 | 3.0 | 36000 | 0.5454 | 0.8476 |
| 0.1436 | 3.17 | 38000 | 0.6787 | 0.8442 |
| 0.1426 | 3.34 | 40000 | 0.6933 | 0.8421 |
| 0.1463 | 3.5 | 42000 | 0.6547 | 0.8455 |
| 0.1447 | 3.67 | 44000 | 0.6469 | 0.8438 |
| 0.1445 | 3.84 | 46000 | 0.6626 | 0.8472 |
| 0.1457 | 4.0 | 48000 | 0.6494 | 0.8504 |
| 0.1133 | 4.17 | 50000 | 0.7664 | 0.8459 |
| 0.1138 | 4.34 | 52000 | 0.7857 | 0.8452 |
| 0.1154 | 4.5 | 54000 | 0.7623 | 0.8486 |
| 0.1102 | 4.67 | 56000 | 0.7740 | 0.8460 |
| 0.1143 | 4.84 | 58000 | 0.7610 | 0.8445 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.12.1
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