File size: 3,453 Bytes
f44ae5b |
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 90 91 |
---
license: mit
base_model: facebook/xlm-v-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-TCR-XLMV_data-en-cardiff_eng_only_beta
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-TCR-XLMV_data-en-cardiff_eng_only_beta
This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface.co/facebook/xlm-v-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4054
- Accuracy: 0.5467
- F1: 0.5510
## 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: 112233
- 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 | 1.03 | 60 | 1.0887 | 0.4449 | 0.3540 |
| No log | 2.07 | 120 | 1.0211 | 0.4700 | 0.3777 |
| No log | 3.1 | 180 | 1.0598 | 0.5141 | 0.4790 |
| No log | 4.14 | 240 | 1.0131 | 0.5644 | 0.5652 |
| No log | 5.17 | 300 | 1.1073 | 0.5586 | 0.5595 |
| No log | 6.21 | 360 | 1.3697 | 0.5635 | 0.5542 |
| No log | 7.24 | 420 | 1.4910 | 0.5379 | 0.5385 |
| No log | 8.28 | 480 | 1.7325 | 0.5507 | 0.5542 |
| 0.6649 | 9.31 | 540 | 1.8878 | 0.5489 | 0.5505 |
| 0.6649 | 10.34 | 600 | 2.2758 | 0.5309 | 0.5320 |
| 0.6649 | 11.38 | 660 | 2.3053 | 0.5357 | 0.5357 |
| 0.6649 | 12.41 | 720 | 2.3674 | 0.5542 | 0.5574 |
| 0.6649 | 13.45 | 780 | 2.7705 | 0.5309 | 0.5332 |
| 0.6649 | 14.48 | 840 | 2.7515 | 0.5520 | 0.5522 |
| 0.6649 | 15.52 | 900 | 2.9868 | 0.5423 | 0.5447 |
| 0.6649 | 16.55 | 960 | 2.7489 | 0.5582 | 0.5597 |
| 0.1079 | 17.59 | 1020 | 2.8748 | 0.5525 | 0.5560 |
| 0.1079 | 18.62 | 1080 | 3.0165 | 0.5467 | 0.5511 |
| 0.1079 | 19.66 | 1140 | 3.2954 | 0.5340 | 0.5356 |
| 0.1079 | 20.69 | 1200 | 3.1051 | 0.5441 | 0.5488 |
| 0.1079 | 21.72 | 1260 | 3.2199 | 0.5441 | 0.5467 |
| 0.1079 | 22.76 | 1320 | 3.1660 | 0.5454 | 0.5500 |
| 0.1079 | 23.79 | 1380 | 3.2637 | 0.5445 | 0.5474 |
| 0.1079 | 24.83 | 1440 | 3.2934 | 0.5538 | 0.5576 |
| 0.0279 | 25.86 | 1500 | 3.2834 | 0.5476 | 0.5506 |
| 0.0279 | 26.9 | 1560 | 3.3734 | 0.5467 | 0.5507 |
| 0.0279 | 27.93 | 1620 | 3.4145 | 0.5437 | 0.5476 |
| 0.0279 | 28.97 | 1680 | 3.4043 | 0.5454 | 0.5496 |
| 0.0279 | 30.0 | 1740 | 3.4054 | 0.5467 | 0.5510 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
|