File size: 2,712 Bytes
39af9ed |
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 |
---
license: mit
base_model: haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-PO-CDF-EN-FROM-CL-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-KD-PO-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only55
This model is a fine-tuned version of [haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only](https://huggingface.co/haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 39.4604
- Accuracy: 0.4537
- F1: 0.4426
## 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 | 1.72 | 100 | 24.2103 | 0.4616 | 0.4518 |
| No log | 3.45 | 200 | 29.3271 | 0.4255 | 0.3714 |
| No log | 5.17 | 300 | 29.8979 | 0.4489 | 0.4414 |
| No log | 6.9 | 400 | 31.7211 | 0.4669 | 0.4627 |
| 15.3839 | 8.62 | 500 | 37.0421 | 0.4581 | 0.4492 |
| 15.3839 | 10.34 | 600 | 32.5884 | 0.4669 | 0.4658 |
| 15.3839 | 12.07 | 700 | 39.9517 | 0.4493 | 0.4332 |
| 15.3839 | 13.79 | 800 | 38.5249 | 0.4630 | 0.4470 |
| 15.3839 | 15.52 | 900 | 38.7918 | 0.4414 | 0.4286 |
| 2.5437 | 17.24 | 1000 | 40.0345 | 0.4524 | 0.4391 |
| 2.5437 | 18.97 | 1100 | 38.3918 | 0.4612 | 0.4527 |
| 2.5437 | 20.69 | 1200 | 41.3974 | 0.4396 | 0.4169 |
| 2.5437 | 22.41 | 1300 | 38.7372 | 0.4603 | 0.4532 |
| 2.5437 | 24.14 | 1400 | 40.1541 | 0.4405 | 0.4288 |
| 1.0429 | 25.86 | 1500 | 40.0459 | 0.4568 | 0.4383 |
| 1.0429 | 27.59 | 1600 | 39.3779 | 0.4590 | 0.4457 |
| 1.0429 | 29.31 | 1700 | 39.4604 | 0.4537 | 0.4426 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
|