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scenario-TCR-XLMV_data-en-cardiff_eng_only_beta2
haryoaw/scenario-TCR-XLMV_data-en-cardiff_eng_only_beta2
scenario-TCR-XLMV_data-en-cardiff_eng_only_beta2 is a text classification model from haryoaw. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Apr 2, 2024
- Updated
- Apr 2, 2024
- SHA
- 8431b67b
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Base models
Model card
From the Hugging Face model README
<!-- 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_beta2
This model is a fine-tuned version of facebook/xlm-v-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0986
- Accuracy: 0.3333
- F1: 0.1667
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: 67
- 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 | 1.0981 | 0.3677 | 0.3195 |
| No log | 2.07 | 120 | 1.0990 | 0.3333 | 0.1667 |
| No log | 3.1 | 180 | 1.0989 | 0.3333 | 0.1667 |
| No log | 4.14 | 240 | 1.0987 | 0.3333 | 0.1667 |
| No log | 5.17 | 300 | 1.0986 | 0.3333 | 0.1667 |
| No log | 6.21 | 360 | 1.0989 | 0.3333 | 0.1667 |
| No log | 7.24 | 420 | 1.0992 | 0.3333 | 0.1667 |
| No log | 8.28 | 480 | 1.0986 | 0.3333 | 0.1667 |
| 1.1002 | 9.31 | 540 | 1.0994 | 0.3333 | 0.1667 |
| 1.1002 | 10.34 | 600 | 1.0987 | 0.3333 | 0.1667 |
| 1.1002 | 11.38 | 660 | 1.0986 | 0.3333 | 0.1667 |
| 1.1002 | 12.41 | 720 | 1.0987 | 0.3333 | 0.1667 |
| 1.1002 | 13.45 | 780 | 1.0987 | 0.3333 | 0.1667 |
| 1.1002 | 14.48 | 840 | 1.0987 | 0.3333 | 0.1667 |
| 1.1002 | 15.52 | 900 | 1.0991 | 0.3333 | 0.1667 |
| 1.1002 | 16.55 | 960 | 1.0988 | 0.3333 | 0.1667 |
| 1.1 | 17.59 | 1020 | 1.0987 | 0.3333 | 0.1667 |
| 1.1 | 18.62 | 1080 | 1.0987 | 0.3333 | 0.1667 |
| 1.1 | 19.66 | 1140 | 1.0988 | 0.3333 | 0.1667 |
| 1.1 | 20.69 | 1200 | 1.0987 | 0.3333 | 0.1667 |
| 1.1 | 21.72 | 1260 | 1.0987 | 0.3333 | 0.1667 |
| 1.1 | 22.76 | 1320 | 1.0986 | 0.3333 | 0.1667 |
| 1.1 | 23.79 | 1380 | 1.0987 | 0.3333 | 0.1667 |
| 1.1 | 24.83 | 1440 | 1.0986 | 0.3333 | 0.1667 |
| 1.0989 | 25.86 | 1500 | 1.0986 | 0.3333 | 0.1667 |
| 1.0989 | 26.9 | 1560 | 1.0986 | 0.3333 | 0.1667 |
| 1.0989 | 27.93 | 1620 | 1.0986 | 0.3333 | 0.1667 |
| 1.0989 | 28.97 | 1680 | 1.0986 | 0.3333 | 0.1667 |
| 1.0989 | 30.0 | 1740 | 1.0986 | 0.3333 | 0.1667 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Apr 2, 2024
- Updated
- Apr 2, 2024