---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: ASAP_FineTuningBERT_UnAugV5_k1_task1_organization_fold0
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ASAP_FineTuningBERT_UnAugV5_k1_task1_organization_fold0

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6550
- Qwk: 0.6278
- Mse: 0.6550
- Rmse: 0.8094

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Qwk    | Mse     | Rmse   |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:------:|
| No log        | 2.0   | 2    | 10.5351         | 0.0061 | 10.5351 | 3.2458 |
| No log        | 4.0   | 4    | 8.2198          | 0.0054 | 8.2198  | 2.8670 |
| No log        | 6.0   | 6    | 6.3796          | 0.0029 | 6.3796  | 2.5258 |
| No log        | 8.0   | 8    | 4.9785          | 0.0139 | 4.9785  | 2.2313 |
| 9.3005        | 10.0  | 10   | 3.7548          | 0.0115 | 3.7548  | 1.9377 |
| 9.3005        | 12.0  | 12   | 2.7153          | 0.0077 | 2.7153  | 1.6478 |
| 9.3005        | 14.0  | 14   | 1.8897          | 0.0520 | 1.8897  | 1.3747 |
| 9.3005        | 16.0  | 16   | 1.3712          | 0.0520 | 1.3712  | 1.1710 |
| 9.3005        | 18.0  | 18   | 1.0739          | 0.0520 | 1.0739  | 1.0363 |
| 3.4599        | 20.0  | 20   | 0.8739          | 0.0664 | 0.8739  | 0.9348 |
| 3.4599        | 22.0  | 22   | 0.7690          | 0.3702 | 0.7690  | 0.8769 |
| 3.4599        | 24.0  | 24   | 0.6434          | 0.4429 | 0.6434  | 0.8021 |
| 3.4599        | 26.0  | 26   | 0.6024          | 0.4529 | 0.6024  | 0.7761 |
| 3.4599        | 28.0  | 28   | 0.5723          | 0.4703 | 0.5723  | 0.7565 |
| 1.4411        | 30.0  | 30   | 0.5559          | 0.5397 | 0.5559  | 0.7456 |
| 1.4411        | 32.0  | 32   | 0.5948          | 0.4984 | 0.5948  | 0.7713 |
| 1.4411        | 34.0  | 34   | 0.5494          | 0.5483 | 0.5494  | 0.7412 |
| 1.4411        | 36.0  | 36   | 0.6670          | 0.5671 | 0.6670  | 0.8167 |
| 1.4411        | 38.0  | 38   | 0.5804          | 0.6215 | 0.5804  | 0.7618 |
| 0.6198        | 40.0  | 40   | 0.7679          | 0.5270 | 0.7679  | 0.8763 |
| 0.6198        | 42.0  | 42   | 0.6548          | 0.5980 | 0.6548  | 0.8092 |
| 0.6198        | 44.0  | 44   | 0.5776          | 0.6053 | 0.5776  | 0.7600 |
| 0.6198        | 46.0  | 46   | 1.0709          | 0.4333 | 1.0709  | 1.0349 |
| 0.6198        | 48.0  | 48   | 1.0767          | 0.4461 | 1.0767  | 1.0376 |
| 0.3311        | 50.0  | 50   | 0.6082          | 0.6208 | 0.6082  | 0.7799 |
| 0.3311        | 52.0  | 52   | 0.6632          | 0.6153 | 0.6632  | 0.8144 |
| 0.3311        | 54.0  | 54   | 0.8101          | 0.5604 | 0.8101  | 0.9000 |
| 0.3311        | 56.0  | 56   | 0.6507          | 0.6362 | 0.6507  | 0.8067 |
| 0.3311        | 58.0  | 58   | 0.7474          | 0.5957 | 0.7474  | 0.8645 |
| 0.1608        | 60.0  | 60   | 0.7510          | 0.5770 | 0.7510  | 0.8666 |
| 0.1608        | 62.0  | 62   | 0.6489          | 0.6265 | 0.6489  | 0.8056 |
| 0.1608        | 64.0  | 64   | 0.8040          | 0.5634 | 0.8040  | 0.8966 |
| 0.1608        | 66.0  | 66   | 0.6306          | 0.6342 | 0.6306  | 0.7941 |
| 0.1608        | 68.0  | 68   | 0.6491          | 0.6393 | 0.6491  | 0.8056 |
| 0.0968        | 70.0  | 70   | 0.8924          | 0.5310 | 0.8924  | 0.9447 |
| 0.0968        | 72.0  | 72   | 0.8359          | 0.5514 | 0.8359  | 0.9143 |
| 0.0968        | 74.0  | 74   | 0.6026          | 0.6239 | 0.6026  | 0.7763 |
| 0.0968        | 76.0  | 76   | 0.5893          | 0.6221 | 0.5893  | 0.7676 |
| 0.0968        | 78.0  | 78   | 0.6519          | 0.6201 | 0.6519  | 0.8074 |
| 0.073         | 80.0  | 80   | 0.9077          | 0.5460 | 0.9077  | 0.9527 |
| 0.073         | 82.0  | 82   | 0.9019          | 0.5462 | 0.9019  | 0.9497 |
| 0.073         | 84.0  | 84   | 0.7039          | 0.6093 | 0.7039  | 0.8390 |
| 0.073         | 86.0  | 86   | 0.6333          | 0.6300 | 0.6333  | 0.7958 |
| 0.073         | 88.0  | 88   | 0.6698          | 0.6237 | 0.6698  | 0.8184 |
| 0.0569        | 90.0  | 90   | 0.7536          | 0.5817 | 0.7536  | 0.8681 |
| 0.0569        | 92.0  | 92   | 0.8272          | 0.5526 | 0.8272  | 0.9095 |
| 0.0569        | 94.0  | 94   | 0.7834          | 0.5585 | 0.7834  | 0.8851 |
| 0.0569        | 96.0  | 96   | 0.7058          | 0.6116 | 0.7058  | 0.8401 |
| 0.0569        | 98.0  | 98   | 0.6605          | 0.6294 | 0.6605  | 0.8127 |
| 0.0526        | 100.0 | 100  | 0.6550          | 0.6278 | 0.6550  | 0.8094 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1