metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
datasets:
- xnli
metrics:
- accuracy
model-index:
- name: checkpoints_xnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: xnli
type: xnli
config: en
split: train
args: en
metrics:
- name: Accuracy
type: accuracy
value: 0.8472664306994984
checkpoints_xnli
This model is a fine-tuned version of xlm-roberta-base on the xnli dataset. It achieves the following results on the evaluation set:
- Loss: 0.4345
- Accuracy: 0.8473
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: 32
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.4929 | 1.0 | 11045 | 0.4551 | 0.8217 |
0.408 | 2.0 | 22090 | 0.4308 | 0.8358 |
0.3093 | 3.0 | 33135 | 0.4345 | 0.8473 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0