File size: 2,841 Bytes
a77f4cb e2cd0ab 63bffed a77f4cb e2cd0ab a77f4cb 63bffed a77f4cb 63bffed a77f4cb 63bffed a77f4cb 63bffed a77f4cb 63bffed a77f4cb 63bffed |
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 |
---
base_model: haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only
library_name: transformers
license: mit
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: scenario-KD-SCR-CDF-EN-FROM-CL-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-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only66
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: 533.1400
- Accuracy: 0.3435
- F1: 0.2746
## 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 | 630.5721 | 0.3347 | 0.2738 |
| No log | 3.4783 | 200 | 605.2021 | 0.3329 | 0.2631 |
| No log | 5.2174 | 300 | 588.4736 | 0.3289 | 0.1894 |
| No log | 6.9565 | 400 | 579.8921 | 0.3302 | 0.2716 |
| 573.1106 | 8.6957 | 500 | 571.2699 | 0.3510 | 0.2838 |
| 573.1106 | 10.4348 | 600 | 564.0858 | 0.3422 | 0.2638 |
| 573.1106 | 12.1739 | 700 | 560.2971 | 0.3364 | 0.2551 |
| 573.1106 | 13.9130 | 800 | 553.0224 | 0.3457 | 0.2748 |
| 573.1106 | 15.6522 | 900 | 549.0078 | 0.3426 | 0.2771 |
| 468.2501 | 17.3913 | 1000 | 545.7394 | 0.3435 | 0.2815 |
| 468.2501 | 19.1304 | 1100 | 541.9386 | 0.3496 | 0.2813 |
| 468.2501 | 20.8696 | 1200 | 539.8362 | 0.3519 | 0.2784 |
| 468.2501 | 22.6087 | 1300 | 537.6076 | 0.3567 | 0.2837 |
| 468.2501 | 24.3478 | 1400 | 535.7779 | 0.3519 | 0.2832 |
| 433.4717 | 26.0870 | 1500 | 533.8346 | 0.3580 | 0.2865 |
| 433.4717 | 27.8261 | 1600 | 533.4024 | 0.3430 | 0.2749 |
| 433.4717 | 29.5652 | 1700 | 533.1400 | 0.3435 | 0.2746 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.19.1
|