metadata
license: mit
base_model: facebook/xlm-v-base
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
- f1
model-index:
- name: scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_alpha2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: massive
type: massive
config: all_1.1
split: validation
args: all_1.1
metrics:
- name: Accuracy
type: accuracy
value: 0.051647811116576486
- name: F1
type: f1
value: 0.0016647904742274576
scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_alpha2
This model is a fine-tuned version of facebook/xlm-v-base on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 3.9116
- Accuracy: 0.0516
- F1: 0.0017
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: 32
- eval_batch_size: 32
- seed: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 500
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
3.7581 | 0.27 | 5000 | 3.7367 | 0.0620 | 0.0020 |
3.7358 | 0.53 | 10000 | 3.7833 | 0.0605 | 0.0019 |
3.7226 | 0.8 | 15000 | 3.7989 | 0.0516 | 0.0017 |
3.7238 | 1.07 | 20000 | 3.8066 | 0.0516 | 0.0017 |
3.727 | 1.34 | 25000 | 3.8172 | 0.0516 | 0.0017 |
3.717 | 1.6 | 30000 | 3.9116 | 0.0516 | 0.0017 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3