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---
license: mit
base_model: haryoaw/scenario-TCR_data-cl-cardiff_cl_only2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PO-CDF-CL-D2_data-cl-cardiff_cl_only_delta-jason
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-CL-D2_data-cl-cardiff_cl_only_delta-jason
This model is a fine-tuned version of [haryoaw/scenario-TCR_data-cl-cardiff_cl_only2](https://huggingface.co/haryoaw/scenario-TCR_data-cl-cardiff_cl_only2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 15.4781
- Accuracy: 0.4043
- F1: 0.3989
## 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: 7777
- 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 | 1.09 | 250 | 11.8950 | 0.3735 | 0.3391 |
| 13.6959 | 2.17 | 500 | 11.1790 | 0.3850 | 0.3767 |
| 13.6959 | 3.26 | 750 | 11.1554 | 0.4082 | 0.4075 |
| 11.138 | 4.35 | 1000 | 11.3070 | 0.4090 | 0.4082 |
| 11.138 | 5.43 | 1250 | 11.4384 | 0.4043 | 0.4029 |
| 9.5889 | 6.52 | 1500 | 11.3483 | 0.4090 | 0.4061 |
| 9.5889 | 7.61 | 1750 | 12.4116 | 0.4020 | 0.3985 |
| 8.2638 | 8.7 | 2000 | 11.7820 | 0.3997 | 0.3798 |
| 8.2638 | 9.78 | 2250 | 11.9709 | 0.4012 | 0.4001 |
| 6.9206 | 10.87 | 2500 | 12.7419 | 0.4198 | 0.4197 |
| 6.9206 | 11.96 | 2750 | 13.1813 | 0.4074 | 0.4078 |
| 5.993 | 13.04 | 3000 | 13.5405 | 0.4074 | 0.4062 |
| 5.993 | 14.13 | 3250 | 13.6698 | 0.3920 | 0.3860 |
| 5.1998 | 15.22 | 3500 | 13.8872 | 0.3989 | 0.3991 |
| 5.1998 | 16.3 | 3750 | 13.8954 | 0.4074 | 0.4076 |
| 4.6117 | 17.39 | 4000 | 14.2214 | 0.4090 | 0.4090 |
| 4.6117 | 18.48 | 4250 | 13.7015 | 0.4097 | 0.4033 |
| 4.0848 | 19.57 | 4500 | 14.8333 | 0.3912 | 0.3798 |
| 4.0848 | 20.65 | 4750 | 14.0279 | 0.4035 | 0.3989 |
| 3.7518 | 21.74 | 5000 | 14.6064 | 0.4035 | 0.4024 |
| 3.7518 | 22.83 | 5250 | 14.6257 | 0.3943 | 0.3914 |
| 3.285 | 23.91 | 5500 | 14.5868 | 0.4020 | 0.3968 |
| 3.285 | 25.0 | 5750 | 15.5230 | 0.3843 | 0.3756 |
| 3.0056 | 26.09 | 6000 | 14.9209 | 0.3904 | 0.3811 |
| 3.0056 | 27.17 | 6250 | 14.9466 | 0.3981 | 0.3968 |
| 2.8364 | 28.26 | 6500 | 15.5711 | 0.3881 | 0.3824 |
| 2.8364 | 29.35 | 6750 | 15.4781 | 0.4043 | 0.3989 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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