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---
license: mit
base_model: haryoaw/scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all_a
tags:
- generated_from_trainer
datasets:
- tweet_sentiment_multilingual
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PO-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_all_gamma
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. -->
# scenario-KD-PO-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_all_gamma
This model is a fine-tuned version of [haryoaw/scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all_a](https://huggingface.co/haryoaw/scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all_a) on the tweet_sentiment_multilingual dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5245
- Accuracy: 0.5517
- F1: 0.5524
## 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: 32
- eval_batch_size: 32
- seed: 88458
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 4.8673 | 1.09 | 500 | 4.1044 | 0.4356 | 0.4381 |
| 4.0355 | 2.17 | 1000 | 3.8162 | 0.5004 | 0.4829 |
| 3.4812 | 3.26 | 1500 | 3.3484 | 0.5312 | 0.5299 |
| 3.1323 | 4.35 | 2000 | 3.3401 | 0.5502 | 0.5500 |
| 2.7632 | 5.43 | 2500 | 3.5126 | 0.5471 | 0.5441 |
| 2.5101 | 6.52 | 3000 | 3.5161 | 0.5444 | 0.5412 |
| 2.3266 | 7.61 | 3500 | 3.6769 | 0.5367 | 0.5263 |
| 2.1096 | 8.7 | 4000 | 3.6299 | 0.5513 | 0.5501 |
| 1.972 | 9.78 | 4500 | 3.4289 | 0.5432 | 0.5428 |
| 1.8345 | 10.87 | 5000 | 3.3890 | 0.5502 | 0.5464 |
| 1.711 | 11.96 | 5500 | 3.3365 | 0.5548 | 0.5553 |
| 1.6043 | 13.04 | 6000 | 3.4657 | 0.5529 | 0.5527 |
| 1.4994 | 14.13 | 6500 | 3.3948 | 0.5494 | 0.5500 |
| 1.404 | 15.22 | 7000 | 3.5906 | 0.5529 | 0.5533 |
| 1.3423 | 16.3 | 7500 | 3.5538 | 0.5575 | 0.5555 |
| 1.2991 | 17.39 | 8000 | 3.5762 | 0.5532 | 0.5539 |
| 1.217 | 18.48 | 8500 | 3.6649 | 0.5517 | 0.5518 |
| 1.1763 | 19.57 | 9000 | 3.5238 | 0.5513 | 0.5503 |
| 1.1249 | 20.65 | 9500 | 3.5218 | 0.5436 | 0.5453 |
| 1.0774 | 21.74 | 10000 | 3.7103 | 0.5617 | 0.5622 |
| 1.0558 | 22.83 | 10500 | 3.6698 | 0.5567 | 0.5558 |
| 1.0036 | 23.91 | 11000 | 3.4754 | 0.5648 | 0.5645 |
| 0.9734 | 25.0 | 11500 | 3.5782 | 0.5490 | 0.5483 |
| 0.9614 | 26.09 | 12000 | 3.4920 | 0.5586 | 0.5600 |
| 0.9221 | 27.17 | 12500 | 3.5416 | 0.5440 | 0.5436 |
| 0.905 | 28.26 | 13000 | 3.5065 | 0.5640 | 0.5635 |
| 0.8845 | 29.35 | 13500 | 3.6653 | 0.5463 | 0.5464 |
| 0.8614 | 30.43 | 14000 | 3.5104 | 0.5583 | 0.5571 |
| 0.8414 | 31.52 | 14500 | 3.6002 | 0.5548 | 0.5554 |
| 0.8328 | 32.61 | 15000 | 3.5431 | 0.5544 | 0.5527 |
| 0.8134 | 33.7 | 15500 | 3.5080 | 0.5590 | 0.5585 |
| 0.7973 | 34.78 | 16000 | 3.4150 | 0.5583 | 0.5578 |
| 0.7887 | 35.87 | 16500 | 3.6270 | 0.5486 | 0.5502 |
| 0.7778 | 36.96 | 17000 | 3.6464 | 0.5494 | 0.5491 |
| 0.7662 | 38.04 | 17500 | 3.5100 | 0.5633 | 0.5627 |
| 0.7553 | 39.13 | 18000 | 3.5580 | 0.5532 | 0.5537 |
| 0.7426 | 40.22 | 18500 | 3.4555 | 0.5594 | 0.5583 |
| 0.7494 | 41.3 | 19000 | 3.5871 | 0.5590 | 0.5554 |
| 0.7252 | 42.39 | 19500 | 3.4094 | 0.5590 | 0.5595 |
| 0.7293 | 43.48 | 20000 | 3.4817 | 0.5656 | 0.5661 |
| 0.7103 | 44.57 | 20500 | 3.4964 | 0.5594 | 0.5596 |
| 0.718 | 45.65 | 21000 | 3.4770 | 0.5598 | 0.5593 |
| 0.7147 | 46.74 | 21500 | 3.4938 | 0.5613 | 0.5616 |
| 0.7014 | 47.83 | 22000 | 3.4664 | 0.5571 | 0.5567 |
| 0.6991 | 48.91 | 22500 | 3.4357 | 0.5606 | 0.5606 |
| 0.6944 | 50.0 | 23000 | 3.5245 | 0.5517 | 0.5524 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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