metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base-finetuned-Adapter-en-ar-mlm-0.15-large-29OCT
results: []
xlm-roberta-base-finetuned-Adapter-en-ar-mlm-0.15-large-29OCT
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2667
- Model Preparation Time: 0.0044
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
|---|---|---|---|---|
| 3.9064 | 0.2498 | 1000 | 3.2366 | 0.0044 |
| 3.0641 | 0.4995 | 2000 | 2.7403 | 0.0044 |
| 2.8162 | 0.7493 | 3000 | 2.5485 | 0.0044 |
| 2.7054 | 0.9990 | 4000 | 2.4384 | 0.0044 |
| 2.6108 | 1.2488 | 5000 | 2.3627 | 0.0044 |
| 2.5357 | 1.4985 | 6000 | 2.3141 | 0.0044 |
| 2.5089 | 1.7483 | 7000 | 2.2847 | 0.0044 |
| 2.4931 | 1.9980 | 8000 | 2.2667 | 0.0044 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.1.1+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1