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---
base_model: bert-base-cased
library_name: peft
license: apache-2.0
metrics:
- f1
tags:
- generated_from_trainer
model-index:
- name: bert-dair-ai-emotion-testing
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. -->
# bert-dair-ai-emotion-testing
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1413
- F1: 0.8670
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.4777 | 1.0 | 48 | 1.1115 | 0.6293 |
| 1.0781 | 2.0 | 96 | 0.7560 | 0.6536 |
| 0.7411 | 3.0 | 144 | 0.6211 | 0.7324 |
| 0.3429 | 4.0 | 192 | 0.4169 | 0.7486 |
| 0.4494 | 5.0 | 240 | 0.2302 | 0.7559 |
| 0.176 | 6.0 | 288 | 0.1959 | 0.8222 |
| 0.1838 | 7.0 | 336 | 0.1578 | 0.8647 |
| 0.1846 | 8.0 | 384 | 0.1451 | 0.8304 |
| 0.1379 | 9.0 | 432 | 0.1554 | 0.8647 |
| 0.0895 | 10.0 | 480 | 0.1418 | 0.8328 |
| 0.0151 | 11.0 | 528 | 0.1468 | 0.8304 |
| 0.0625 | 12.0 | 576 | 0.1630 | 0.8304 |
| 0.0397 | 13.0 | 624 | 0.1372 | 0.8304 |
| 0.0177 | 14.0 | 672 | 0.1359 | 0.8304 |
| 0.0062 | 15.0 | 720 | 0.1386 | 0.8328 |
| 0.0244 | 16.0 | 768 | 0.1298 | 0.8351 |
| 0.01 | 17.0 | 816 | 0.1369 | 0.8351 |
| 0.0094 | 18.0 | 864 | 0.1418 | 0.8670 |
| 0.0329 | 19.0 | 912 | 0.1400 | 0.8670 |
| 0.0791 | 20.0 | 960 | 0.1413 | 0.8670 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.48.0
- Pytorch 2.4.1+cu124
- Datasets 3.0.1
- Tokenizers 0.21.0 |