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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_gamma-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_gamma-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: 17.5985
- Accuracy: 0.3958
- F1: 0.3956
## 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: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 1.09 | 250 | 11.6483 | 0.3650 | 0.3609 |
| 13.703 | 2.17 | 500 | 11.1328 | 0.3843 | 0.3821 |
| 13.703 | 3.26 | 750 | 10.9310 | 0.3997 | 0.3991 |
| 11.1159 | 4.35 | 1000 | 11.8248 | 0.4035 | 0.3976 |
| 11.1159 | 5.43 | 1250 | 11.2452 | 0.4074 | 0.4047 |
| 9.5324 | 6.52 | 1500 | 12.0093 | 0.4082 | 0.4079 |
| 9.5324 | 7.61 | 1750 | 12.4283 | 0.4043 | 0.4042 |
| 8.2184 | 8.7 | 2000 | 12.1651 | 0.3897 | 0.3860 |
| 8.2184 | 9.78 | 2250 | 13.2395 | 0.4012 | 0.4006 |
| 7.0214 | 10.87 | 2500 | 13.4757 | 0.4028 | 0.4030 |
| 7.0214 | 11.96 | 2750 | 14.5726 | 0.3943 | 0.3878 |
| 6.0532 | 13.04 | 3000 | 15.9024 | 0.3966 | 0.3918 |
| 6.0532 | 14.13 | 3250 | 16.2467 | 0.3819 | 0.3672 |
| 5.3338 | 15.22 | 3500 | 14.5700 | 0.3912 | 0.3911 |
| 5.3338 | 16.3 | 3750 | 14.7870 | 0.3989 | 0.3969 |
| 4.7168 | 17.39 | 4000 | 16.6837 | 0.3804 | 0.3758 |
| 4.7168 | 18.48 | 4250 | 16.3479 | 0.3835 | 0.3807 |
| 4.052 | 19.57 | 4500 | 16.3096 | 0.3897 | 0.3860 |
| 4.052 | 20.65 | 4750 | 16.4666 | 0.3958 | 0.3947 |
| 3.6691 | 21.74 | 5000 | 16.7052 | 0.3935 | 0.3851 |
| 3.6691 | 22.83 | 5250 | 16.9439 | 0.4012 | 0.3985 |
| 3.3107 | 23.91 | 5500 | 16.8777 | 0.4051 | 0.4025 |
| 3.3107 | 25.0 | 5750 | 17.4662 | 0.3897 | 0.3866 |
| 2.9893 | 26.09 | 6000 | 17.5858 | 0.3951 | 0.3939 |
| 2.9893 | 27.17 | 6250 | 17.6884 | 0.3935 | 0.3928 |
| 2.8471 | 28.26 | 6500 | 17.7042 | 0.3881 | 0.3871 |
| 2.8471 | 29.35 | 6750 | 17.5985 | 0.3958 | 0.3956 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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