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# bertweet-finetuned_twitch-sentiment-analysis

This model is a fine-tuned version of [finiteautomata/bertweet-base-sentiment-analysis](https://huggingface.co/finiteautomata/bertweet-base-sentiment-analysis) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3828
- Accuracy: 0.6513
- F1: 0.6513

## 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: 16
- eval_batch_size: 16
- 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 | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 79   | 0.9173          | 0.5424   | 0.5424 |
| 0.9476        | 2.0   | 158  | 0.9454          | 0.5701   | 0.5701 |
| 0.8032        | 3.0   | 237  | 0.8781          | 0.6107   | 0.6107 |
| 0.7289        | 4.0   | 316  | 0.9143          | 0.6218   | 0.6218 |
| 0.7289        | 5.0   | 395  | 0.8310          | 0.6513   | 0.6513 |
| 0.5873        | 6.0   | 474  | 0.9353          | 0.6624   | 0.6624 |
| 0.4568        | 7.0   | 553  | 0.9365          | 0.6734   | 0.6734 |
| 0.3544        | 8.0   | 632  | 1.0126          | 0.6494   | 0.6494 |
| 0.3161        | 9.0   | 711  | 1.0378          | 0.6494   | 0.6494 |
| 0.3161        | 10.0  | 790  | 1.2249          | 0.6568   | 0.6568 |
| 0.2757        | 11.0  | 869  | 1.1352          | 0.6808   | 0.6808 |
| 0.2619        | 12.0  | 948  | 1.2467          | 0.6697   | 0.6697 |
| 0.2292        | 13.0  | 1027 | 1.3262          | 0.6716   | 0.6716 |
| 0.2115        | 14.0  | 1106 | 1.3367          | 0.6697   | 0.6697 |
| 0.2115        | 15.0  | 1185 | 1.3757          | 0.6882   | 0.6882 |
| 0.1848        | 16.0  | 1264 | 1.3650          | 0.6697   | 0.6697 |
| 0.1916        | 17.0  | 1343 | 1.4940          | 0.6587   | 0.6587 |
| 0.1734        | 18.0  | 1422 | 1.5929          | 0.6808   | 0.6808 |
| 0.1715        | 19.0  | 1501 | 1.5662          | 0.6734   | 0.6734 |
| 0.1715        | 20.0  | 1580 | 1.6073          | 0.6845   | 0.6845 |
| 0.1711        | 21.0  | 1659 | 1.5038          | 0.6808   | 0.6808 |
| 0.1735        | 22.0  | 1738 | 1.8104          | 0.6587   | 0.6587 |
| 0.142         | 23.0  | 1817 | 1.4715          | 0.6900   | 0.6900 |
| 0.142         | 24.0  | 1896 | 1.7028          | 0.6863   | 0.6863 |
| 0.1504        | 25.0  | 1975 | 1.5413          | 0.6900   | 0.6900 |
| 0.1536        | 26.0  | 2054 | 1.7148          | 0.6624   | 0.6624 |
| 0.1405        | 27.0  | 2133 | 1.5510          | 0.6624   | 0.6624 |
| 0.1296        | 28.0  | 2212 | 1.6857          | 0.6863   | 0.6863 |
| 0.1296        | 29.0  | 2291 | 1.6228          | 0.6679   | 0.6679 |
| 0.1247        | 30.0  | 2370 | 1.7248          | 0.6716   | 0.6716 |
| 0.1181        | 31.0  | 2449 | 1.7833          | 0.6716   | 0.6716 |
| 0.1342        | 32.0  | 2528 | 1.9463          | 0.6661   | 0.6661 |
| 0.1412        | 33.0  | 2607 | 1.9416          | 0.6734   | 0.6734 |
| 0.1412        | 34.0  | 2686 | 1.7277          | 0.6679   | 0.6679 |
| 0.1114        | 35.0  | 2765 | 1.7833          | 0.6734   | 0.6734 |
| 0.1139        | 36.0  | 2844 | 1.8031          | 0.6753   | 0.6753 |
| 0.1143        | 37.0  | 2923 | 1.7150          | 0.6716   | 0.6716 |
| 0.1031        | 38.0  | 3002 | 1.9060          | 0.6827   | 0.6827 |
| 0.1031        | 39.0  | 3081 | 1.8854          | 0.6587   | 0.6587 |
| 0.1162        | 40.0  | 3160 | 1.8868          | 0.6753   | 0.6753 |
| 0.1115        | 41.0  | 3239 | 1.7967          | 0.6808   | 0.6808 |
| 0.1118        | 42.0  | 3318 | 1.9692          | 0.6661   | 0.6661 |
| 0.1118        | 43.0  | 3397 | 1.9876          | 0.6661   | 0.6661 |
| 0.1017        | 44.0  | 3476 | 1.9332          | 0.6642   | 0.6642 |
| 0.1172        | 45.0  | 3555 | 1.8807          | 0.6679   | 0.6679 |
| 0.1128        | 46.0  | 3634 | 1.9357          | 0.7011   | 0.7011 |
| 0.1196        | 47.0  | 3713 | 2.0208          | 0.6679   | 0.6679 |
| 0.1196        | 48.0  | 3792 | 1.9668          | 0.6679   | 0.6679 |
| 0.0955        | 49.0  | 3871 | 2.0051          | 0.6661   | 0.6661 |
| 0.0959        | 50.0  | 3950 | 1.9267          | 0.6661   | 0.6661 |
| 0.1144        | 51.0  | 4029 | 2.0940          | 0.6716   | 0.6716 |
| 0.107         | 52.0  | 4108 | 2.1097          | 0.6697   | 0.6697 |
| 0.107         | 53.0  | 4187 | 2.0383          | 0.6624   | 0.6624 |
| 0.1176        | 54.0  | 4266 | 1.9996          | 0.6587   | 0.6587 |
| 0.112         | 55.0  | 4345 | 2.0815          | 0.6716   | 0.6716 |
| 0.1033        | 56.0  | 4424 | 1.8365          | 0.6661   | 0.6661 |
| 0.116         | 57.0  | 4503 | 2.0785          | 0.6679   | 0.6679 |
| 0.116         | 58.0  | 4582 | 2.0580          | 0.6624   | 0.6624 |
| 0.1048        | 59.0  | 4661 | 2.0619          | 0.6863   | 0.6863 |
| 0.0907        | 60.0  | 4740 | 2.0260          | 0.6753   | 0.6753 |
| 0.1021        | 61.0  | 4819 | 2.0572          | 0.6753   | 0.6753 |
| 0.1021        | 62.0  | 4898 | 1.9949          | 0.6753   | 0.6753 |
| 0.0921        | 63.0  | 4977 | 2.0043          | 0.6808   | 0.6808 |
| 0.099         | 64.0  | 5056 | 2.1510          | 0.6697   | 0.6697 |
| 0.0792        | 65.0  | 5135 | 2.1658          | 0.6642   | 0.6642 |
| 0.1056        | 66.0  | 5214 | 2.0118          | 0.6734   | 0.6734 |
| 0.1056        | 67.0  | 5293 | 2.1683          | 0.6661   | 0.6661 |
| 0.0994        | 68.0  | 5372 | 2.1810          | 0.6734   | 0.6734 |
| 0.1054        | 69.0  | 5451 | 2.0225          | 0.6900   | 0.6900 |
| 0.0975        | 70.0  | 5530 | 2.1230          | 0.6679   | 0.6679 |
| 0.0885        | 71.0  | 5609 | 2.0770          | 0.6808   | 0.6808 |
| 0.0885        | 72.0  | 5688 | 2.0654          | 0.6771   | 0.6771 |
| 0.0939        | 73.0  | 5767 | 2.1239          | 0.6624   | 0.6624 |
| 0.1028        | 74.0  | 5846 | 2.1897          | 0.6771   | 0.6771 |
| 0.0851        | 75.0  | 5925 | 2.0848          | 0.6790   | 0.6790 |
| 0.0783        | 76.0  | 6004 | 2.1199          | 0.6734   | 0.6734 |
| 0.0783        | 77.0  | 6083 | 2.2011          | 0.6734   | 0.6734 |
| 0.0874        | 78.0  | 6162 | 2.1734          | 0.6679   | 0.6679 |
| 0.0878        | 79.0  | 6241 | 2.1986          | 0.6624   | 0.6624 |
| 0.0939        | 80.0  | 6320 | 2.2401          | 0.6642   | 0.6642 |
| 0.0939        | 81.0  | 6399 | 2.3477          | 0.6605   | 0.6605 |
| 0.0835        | 82.0  | 6478 | 2.3740          | 0.6605   | 0.6605 |
| 0.0887        | 83.0  | 6557 | 2.3200          | 0.6661   | 0.6661 |
| 0.0943        | 84.0  | 6636 | 2.3248          | 0.6642   | 0.6642 |
| 0.0875        | 85.0  | 6715 | 2.3079          | 0.6605   | 0.6605 |
| 0.0875        | 86.0  | 6794 | 2.3209          | 0.6568   | 0.6568 |
| 0.0822        | 87.0  | 6873 | 2.3303          | 0.6587   | 0.6587 |
| 0.0846        | 88.0  | 6952 | 2.3620          | 0.6531   | 0.6531 |
| 0.0909        | 89.0  | 7031 | 2.3498          | 0.6587   | 0.6587 |
| 0.0871        | 90.0  | 7110 | 2.3323          | 0.6513   | 0.6513 |
| 0.0871        | 91.0  | 7189 | 2.3494          | 0.6513   | 0.6513 |
| 0.0796        | 92.0  | 7268 | 2.3677          | 0.6513   | 0.6513 |
| 0.0797        | 93.0  | 7347 | 2.3887          | 0.6513   | 0.6513 |
| 0.0959        | 94.0  | 7426 | 2.3747          | 0.6513   | 0.6513 |
| 0.0861        | 95.0  | 7505 | 2.3896          | 0.6550   | 0.6550 |
| 0.0861        | 96.0  | 7584 | 2.3786          | 0.6531   | 0.6531 |
| 0.089         | 97.0  | 7663 | 2.3692          | 0.6531   | 0.6531 |
| 0.0764        | 98.0  | 7742 | 2.3789          | 0.6494   | 0.6494 |
| 0.0874        | 99.0  | 7821 | 2.3833          | 0.6513   | 0.6513 |
| 0.0852        | 100.0 | 7900 | 2.3828          | 0.6513   | 0.6513 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "finiteautomata/bertweet-base-sentiment-analysis", "model-index": [{"name": "bertweet-finetuned_twitch-sentiment-analysis", "results": []}]}
transformers safetensors roberta text-classification generated_from_trainer base_model:finiteautomata/bertweet-base-sentiment-analysis autotrain_compatible endpoints_compatible region:us