---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: ASAP_FineTuningBERT_AugV5_k1_task1_organization_fold3
  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. -->

# ASAP_FineTuningBERT_AugV5_k1_task1_organization_fold3

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: 0.5472
- Qwk: 0.6157
- Mse: 0.5468
- Rmse: 0.7395

## 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    | 10.1792         | 0.0    | 10.1785 | 3.1904 |
| No log        | 4.0   | 4    | 8.5089          | 0.0    | 8.5083  | 2.9169 |
| No log        | 6.0   | 6    | 6.9593          | 0.0    | 6.9588  | 2.6380 |
| No log        | 8.0   | 8    | 5.4856          | 0.0235 | 5.4854  | 2.3421 |
| 8.9084        | 10.0  | 10   | 4.5301          | 0.0076 | 4.5301  | 2.1284 |
| 8.9084        | 12.0  | 12   | 3.7061          | 0.0    | 3.7062  | 1.9252 |
| 8.9084        | 14.0  | 14   | 3.0780          | 0.0    | 3.0783  | 1.7545 |
| 8.9084        | 16.0  | 16   | 2.4917          | 0.0806 | 2.4921  | 1.5786 |
| 8.9084        | 18.0  | 18   | 2.0632          | 0.0462 | 2.0637  | 1.4365 |
| 4.248         | 20.0  | 20   | 1.7062          | 0.0365 | 1.7068  | 1.3064 |
| 4.248         | 22.0  | 22   | 1.4205          | 0.0266 | 1.4211  | 1.1921 |
| 4.248         | 24.0  | 24   | 1.2230          | 0.0365 | 1.2236  | 1.1062 |
| 4.248         | 26.0  | 26   | 1.0188          | 0.0266 | 1.0194  | 1.0097 |
| 4.248         | 28.0  | 28   | 0.9326          | 0.1345 | 0.9331  | 0.9660 |
| 2.2317        | 30.0  | 30   | 0.7686          | 0.4194 | 0.7691  | 0.8770 |
| 2.2317        | 32.0  | 32   | 0.6643          | 0.4239 | 0.6649  | 0.8154 |
| 2.2317        | 34.0  | 34   | 0.6961          | 0.4841 | 0.6964  | 0.8345 |
| 2.2317        | 36.0  | 36   | 0.5712          | 0.4966 | 0.5715  | 0.7560 |
| 2.2317        | 38.0  | 38   | 0.5742          | 0.4828 | 0.5746  | 0.7580 |
| 1.1982        | 40.0  | 40   | 0.6294          | 0.5328 | 0.6296  | 0.7935 |
| 1.1982        | 42.0  | 42   | 0.5522          | 0.5493 | 0.5524  | 0.7432 |
| 1.1982        | 44.0  | 44   | 0.5565          | 0.5326 | 0.5567  | 0.7461 |
| 1.1982        | 46.0  | 46   | 0.5330          | 0.6138 | 0.5330  | 0.7300 |
| 1.1982        | 48.0  | 48   | 0.5267          | 0.6243 | 0.5266  | 0.7257 |
| 0.6088        | 50.0  | 50   | 0.5512          | 0.6109 | 0.5512  | 0.7424 |
| 0.6088        | 52.0  | 52   | 0.5308          | 0.6299 | 0.5307  | 0.7285 |
| 0.6088        | 54.0  | 54   | 0.5550          | 0.6454 | 0.5548  | 0.7449 |
| 0.6088        | 56.0  | 56   | 0.5786          | 0.6130 | 0.5783  | 0.7605 |
| 0.6088        | 58.0  | 58   | 0.5721          | 0.6516 | 0.5719  | 0.7562 |
| 0.3243        | 60.0  | 60   | 0.5806          | 0.6334 | 0.5804  | 0.7618 |
| 0.3243        | 62.0  | 62   | 0.5647          | 0.6108 | 0.5644  | 0.7513 |
| 0.3243        | 64.0  | 64   | 0.5766          | 0.6371 | 0.5762  | 0.7591 |
| 0.3243        | 66.0  | 66   | 0.6710          | 0.6038 | 0.6707  | 0.8190 |
| 0.3243        | 68.0  | 68   | 0.6148          | 0.6469 | 0.6144  | 0.7838 |
| 0.2165        | 70.0  | 70   | 0.6383          | 0.6439 | 0.6378  | 0.7986 |
| 0.2165        | 72.0  | 72   | 0.6265          | 0.6445 | 0.6259  | 0.7912 |
| 0.2165        | 74.0  | 74   | 0.5973          | 0.6427 | 0.5968  | 0.7725 |
| 0.2165        | 76.0  | 76   | 0.5642          | 0.6337 | 0.5638  | 0.7509 |
| 0.2165        | 78.0  | 78   | 0.6005          | 0.6137 | 0.6001  | 0.7747 |
| 0.1667        | 80.0  | 80   | 0.5892          | 0.6100 | 0.5889  | 0.7674 |
| 0.1667        | 82.0  | 82   | 0.5564          | 0.6097 | 0.5561  | 0.7457 |
| 0.1667        | 84.0  | 84   | 0.5499          | 0.6275 | 0.5496  | 0.7413 |
| 0.1667        | 86.0  | 86   | 0.5634          | 0.6148 | 0.5630  | 0.7503 |
| 0.1667        | 88.0  | 88   | 0.5774          | 0.6205 | 0.5770  | 0.7596 |
| 0.1285        | 90.0  | 90   | 0.5857          | 0.6113 | 0.5852  | 0.7650 |
| 0.1285        | 92.0  | 92   | 0.5637          | 0.6233 | 0.5633  | 0.7505 |
| 0.1285        | 94.0  | 94   | 0.5507          | 0.6195 | 0.5502  | 0.7418 |
| 0.1285        | 96.0  | 96   | 0.5484          | 0.6197 | 0.5480  | 0.7403 |
| 0.1285        | 98.0  | 98   | 0.5466          | 0.6224 | 0.5462  | 0.7390 |
| 0.0925        | 100.0 | 100  | 0.5472          | 0.6157 | 0.5468  | 0.7395 |


### Framework versions

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