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_gamma2
    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: 0.8497862196829241
          - name: F1
            type: f1
            value: 0.8128154197258449

scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_gamma2

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: 0.7609
Accuracy: 0.8498
F1: 0.8128

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: 77
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
0.6302	0.27	5000	0.7304	0.8189	0.7638
0.4558	0.53	10000	0.6614	0.8412	0.7995
0.3573	0.8	15000	0.6639	0.8461	0.8146
0.2797	1.07	20000	0.7008	0.8485	0.8198
0.2779	1.34	25000	0.7087	0.8484	0.8225
0.2658	1.6	30000	0.7185	0.8509	0.8235
0.2488	1.87	35000	0.7334	0.8486	0.8229
0.2027	2.14	40000	0.8087	0.8458	0.8201
0.2112	2.41	45000	0.7449	0.8501	0.8228
0.2013	2.67	50000	0.7695	0.8502	0.8203
0.2065	2.94	55000	0.7609	0.8498	0.8128

Framework versions

Transformers 4.33.3
Pytorch 2.1.1+cu121
Datasets 2.14.5
Tokenizers 0.13.3