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tir-xlm-focal-lr-3e-5
jaycentg/tir-xlm-focal-lr-3e-5
tir-xlm-focal-lr-3e-5 is a text classification model from jaycentg. 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
- Jan 23, 2025
- Updated
- Jan 23, 2025
- SHA
- dcb80132
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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. -->
tir-xlm-focal-lr-3e-5
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 13.9432
- F1-micro: 0.1908
- F1-macro: 0.2089
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 73
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | F1-micro | F1-macro |
|---|---|---|---|---|---|
| 39.9906 | 1.0 | 184 | 14.0643 | 0.2948 | 0.1618 |
| 39.8656 | 2.0 | 368 | 13.8770 | 0.2704 | 0.2618 |
| 39.8165 | 3.0 | 552 | 14.0230 | 0.2450 | 0.2243 |
| 39.7675 | 4.0 | 736 | 13.9432 | 0.1908 | 0.2089 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jan 23, 2025
- Updated
- Jan 23, 2025