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---
library_name: transformers
license: mit
base_model: haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-NON-KD-PO-COPY-CDF-EN-D2_data-en-cardiff_eng_only55
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-NON-KD-PO-COPY-CDF-EN-D2_data-en-cardiff_eng_only55
This model is a fine-tuned version of [haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only](https://huggingface.co/haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 5.0027
- Accuracy: 0.4656
- F1: 0.4619
## 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: 55
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| No log | 1.7241 | 100 | 1.2748 | 0.4339 | 0.4142 |
| No log | 3.4483 | 200 | 1.3406 | 0.4660 | 0.4596 |
| No log | 5.1724 | 300 | 1.5563 | 0.4757 | 0.4694 |
| No log | 6.8966 | 400 | 2.0113 | 0.4683 | 0.4688 |
| 0.5741 | 8.6207 | 500 | 2.4441 | 0.4700 | 0.4666 |
| 0.5741 | 10.3448 | 600 | 2.6979 | 0.4656 | 0.4657 |
| 0.5741 | 12.0690 | 700 | 3.3013 | 0.4630 | 0.4595 |
| 0.5741 | 13.7931 | 800 | 3.6311 | 0.4652 | 0.4630 |
| 0.5741 | 15.5172 | 900 | 4.2150 | 0.4537 | 0.4431 |
| 0.0798 | 17.2414 | 1000 | 4.2688 | 0.4581 | 0.4507 |
| 0.0798 | 18.9655 | 1100 | 4.4930 | 0.4630 | 0.4597 |
| 0.0798 | 20.6897 | 1200 | 4.8125 | 0.4537 | 0.4398 |
| 0.0798 | 22.4138 | 1300 | 4.7923 | 0.4674 | 0.4603 |
| 0.0798 | 24.1379 | 1400 | 4.8840 | 0.4616 | 0.4594 |
| 0.0132 | 25.8621 | 1500 | 5.0249 | 0.4612 | 0.4539 |
| 0.0132 | 27.5862 | 1600 | 5.0564 | 0.4594 | 0.4534 |
| 0.0132 | 29.3103 | 1700 | 5.0027 | 0.4656 | 0.4619 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.19.1
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