Downloads · 30 days
26
33% of all-time downloads
xmod-roberta-base-legal-multi-indian-downstream-ildc
MHGanainy/xmod-roberta-base-legal-multi-indian-downstream-ildc
xmod-roberta-base-legal-multi-indian-downstream-ildc is a text classification model from MHGanainy. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
80
Public
Parameters
167M
4.7 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors669 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- xmod
- Access
- Public
- Created
- Aug 27, 2024
- Updated
- Aug 27, 2024
- SHA
- e236e8e3
Try a prompt
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. -->
xmod-roberta-base-legal-multi-indian-downstream-ildc
This model is a fine-tuned version of MHGanainy/xmod-roberta-base-legal-multi on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5502
- Accuracy: 0.8119
- Precision: 0.7808
- Recall: 0.8672
- F1: 0.8217
- Best Threshold: 0.2288
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: 16
- seed: 1
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Best Threshold |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 253 | 0.5711 | 0.6911 | 0.6518 | 0.8209 | 0.7266 | 0.3842 |
| 0.6167 | 2.0 | 506 | 0.4499 | 0.8169 | 0.7869 | 0.8692 | 0.8260 | 0.2500 |
| 0.6167 | 3.0 | 759 | 0.4771 | 0.8209 | 0.8235 | 0.8169 | 0.8202 | 0.2625 |
| 0.4511 | 4.0 | 1012 | 0.4272 | 0.8320 | 0.8367 | 0.8249 | 0.8308 | 0.3866 |
| 0.4511 | 5.0 | 1265 | 0.4464 | 0.8249 | 0.8276 | 0.8209 | 0.8242 | 0.4329 |
| 0.348 | 6.0 | 1518 | 0.5935 | 0.8008 | 0.7984 | 0.8048 | 0.8016 | 0.2162 |
| 0.348 | 7.0 | 1771 | 0.5502 | 0.8119 | 0.7808 | 0.8672 | 0.8217 | 0.2288 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- xmod
- Created
- Aug 27, 2024
- Updated
- Aug 27, 2024