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M365_h1_retrained_v1
marklicata/M365_h1_retrained_v1
M365_h1_retrained_v1 is a text classification model from marklicata. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Nov 27, 2024
- Updated
- Nov 27, 2024
- SHA
- 0127d512
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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. -->
M365_h1_v1
This model is a fine-tuned version of marklicata/M365_h1_base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0058
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2553 | 1.0 | 800 | 0.0057 |
| 0.0001 | 2.0 | 1600 | 0.0055 |
| 0.0001 | 3.0 | 2400 | 0.0058 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cpu
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Nov 27, 2024
- Updated
- Nov 27, 2024