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mtl-xlmr-base-viwiki
MiuN2k3/mtl-xlmr-base-viwiki
mtl-xlmr-base-viwiki is a machine learning model from MiuN2k3. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Jun 8, 2024
- Updated
- Jun 16, 2024
- SHA
- 743d4fda
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. -->
mtl-xlmr-base-viwiki
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6233
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9031 | 1.0 | 963 | 0.8264 |
| 0.6923 | 2.0 | 1926 | 0.7016 |
| 0.644 | 3.0 | 2889 | 0.6884 |
| 0.5999 | 4.0 | 3852 | 0.6142 |
| 0.5781 | 5.0 | 4815 | 0.6233 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.2.1
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Jun 8, 2024
- Updated
- Jun 16, 2024