metadata
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
model-index:
- name: results
results: []
results
This model is a fine-tuned version of xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 1.9243
- eval_accuracy: 0.1677
- eval_f1: 0.0482
- eval_precision: 0.0281
- eval_recall: 0.1677
- eval_runtime: 27.8461
- eval_samples_per_second: 41.334
- eval_steps_per_second: 10.343
- epoch: 2.0
- step: 3064
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1