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---
base_model: haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only
library_name: transformers
license: mit
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: scenario-KD-SCR-PO-CDF-EN-FROM-EN-D2_data-en-cardiff_eng_only66
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-SCR-PO-CDF-EN-FROM-EN-D2_data-en-cardiff_eng_only66
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: 533.0406
- Accuracy: 0.3444
- F1: 0.2711
## 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: 8
- eval_batch_size: 32
- seed: 66
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 | 1.7391 | 100 | 631.4247 | 0.3302 | 0.2694 |
| No log | 3.4783 | 200 | 605.5723 | 0.3413 | 0.2651 |
| No log | 5.2174 | 300 | 589.1194 | 0.3369 | 0.2521 |
| No log | 6.9565 | 400 | 580.2668 | 0.3501 | 0.2633 |
| 574.1509 | 8.6957 | 500 | 571.8079 | 0.3254 | 0.2189 |
| 574.1509 | 10.4348 | 600 | 564.8586 | 0.3360 | 0.2072 |
| 574.1509 | 12.1739 | 700 | 559.2232 | 0.3417 | 0.2567 |
| 574.1509 | 13.9130 | 800 | 552.7770 | 0.3391 | 0.2289 |
| 574.1509 | 15.6522 | 900 | 549.6864 | 0.3333 | 0.2295 |
| 468.9151 | 17.3913 | 1000 | 545.1831 | 0.3338 | 0.2429 |
| 468.9151 | 19.1304 | 1100 | 541.3506 | 0.3466 | 0.2794 |
| 468.9151 | 20.8696 | 1200 | 538.9130 | 0.3355 | 0.2612 |
| 468.9151 | 22.6087 | 1300 | 537.2876 | 0.3470 | 0.2807 |
| 468.9151 | 24.3478 | 1400 | 535.7286 | 0.3426 | 0.2346 |
| 433.9469 | 26.0870 | 1500 | 533.7326 | 0.3492 | 0.2730 |
| 433.9469 | 27.8261 | 1600 | 533.2730 | 0.3338 | 0.2553 |
| 433.9469 | 29.5652 | 1700 | 533.0406 | 0.3444 | 0.2711 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.19.1
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