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roberta-large-aphasia-picture-description-10e
Middelz2/roberta-large-aphasia-picture-description-10e
roberta-large-aphasia-picture-description-10e is a fill-mask model from Middelz2. Use it when you need the model to fill a missing word. It is set up for transformers. The card lists the license as mit.
probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Fill-Mask
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- May 24, 2023
- Updated
- May 24, 2023
- SHA
- 0ff97c3b
Try a prompt
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
Middelz2/roberta-large-aphasia-picture-description-10e
This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 1.0392
- Validation Loss: 0.9399
- Epoch: 9
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 1.5600 | 1.2996 | 0 |
| 1.3034 | 1.2214 | 1 |
| 1.2276 | 1.1589 | 2 |
| 1.1964 | 1.0836 | 3 |
| 1.1387 | 1.0659 | 4 |
| 1.1209 | 1.0436 | 5 |
| 1.0559 | 1.0221 | 6 |
| 1.0564 | 0.9269 | 7 |
| 1.0227 | 0.9755 | 8 |
| 1.0392 | 0.9399 | 9 |
Framework versions
- Transformers 4.29.2
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Fill-Mask
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- May 24, 2023
- Updated
- May 24, 2023