File size: 3,414 Bytes
1abb588 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 |
---
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_alpha-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_alpha-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: 16.1676
- Accuracy: 0.4005
- F1: 0.3988
## 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: 2222
- 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 | 11.7802 | 0.3727 | 0.3689 |
| 13.6353 | 2.17 | 500 | 10.9269 | 0.4120 | 0.4013 |
| 13.6353 | 3.26 | 750 | 10.7530 | 0.4066 | 0.4034 |
| 11.1498 | 4.35 | 1000 | 11.4698 | 0.4059 | 0.3994 |
| 11.1498 | 5.43 | 1250 | 11.1047 | 0.4182 | 0.4140 |
| 9.4007 | 6.52 | 1500 | 11.6114 | 0.4028 | 0.3911 |
| 9.4007 | 7.61 | 1750 | 12.1035 | 0.3935 | 0.3911 |
| 8.1024 | 8.7 | 2000 | 13.1654 | 0.4090 | 0.4035 |
| 8.1024 | 9.78 | 2250 | 12.8799 | 0.4020 | 0.4001 |
| 7.094 | 10.87 | 2500 | 12.5580 | 0.4082 | 0.3972 |
| 7.094 | 11.96 | 2750 | 12.7991 | 0.4228 | 0.4214 |
| 6.1021 | 13.04 | 3000 | 13.4827 | 0.3920 | 0.3906 |
| 6.1021 | 14.13 | 3250 | 14.8695 | 0.4159 | 0.4135 |
| 5.1725 | 15.22 | 3500 | 14.0881 | 0.4090 | 0.4081 |
| 5.1725 | 16.3 | 3750 | 14.4576 | 0.3866 | 0.3782 |
| 4.616 | 17.39 | 4000 | 14.4197 | 0.3819 | 0.3777 |
| 4.616 | 18.48 | 4250 | 15.2137 | 0.3997 | 0.3986 |
| 4.0484 | 19.57 | 4500 | 15.2744 | 0.3943 | 0.3939 |
| 4.0484 | 20.65 | 4750 | 15.3068 | 0.3858 | 0.3840 |
| 3.6271 | 21.74 | 5000 | 16.0691 | 0.4059 | 0.4030 |
| 3.6271 | 22.83 | 5250 | 15.7583 | 0.4120 | 0.4120 |
| 3.3297 | 23.91 | 5500 | 15.9934 | 0.4028 | 0.4002 |
| 3.3297 | 25.0 | 5750 | 16.3662 | 0.4097 | 0.4092 |
| 3.0762 | 26.09 | 6000 | 16.4914 | 0.4051 | 0.4040 |
| 3.0762 | 27.17 | 6250 | 16.4281 | 0.4051 | 0.4043 |
| 2.8363 | 28.26 | 6500 | 16.3025 | 0.4151 | 0.4149 |
| 2.8363 | 29.35 | 6750 | 16.1676 | 0.4005 | 0.3988 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
|