metadata

license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: fb-data2vec-finetuned-finance-classification
    results: []

fb-data2vec-finetuned-finance-classification

This model is a fine-tuned version of facebook/data2vec-text-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.8993
Accuracy: 0.8557
F1: 0.8563
Precision: 0.8576
Recall: 0.8557

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	285	0.6704	0.6680	0.6262	0.7919	0.6680
0.6626	2.0	570	0.4731	0.8360	0.8350	0.8346	0.8360
0.6626	3.0	855	0.4598	0.8458	0.8454	0.8452	0.8458
0.3666	4.0	1140	0.4758	0.8360	0.8352	0.8353	0.8360
0.3666	5.0	1425	0.5683	0.8340	0.8342	0.8353	0.8340
0.2316	6.0	1710	0.6234	0.8419	0.8421	0.8447	0.8419
0.2316	7.0	1995	0.7186	0.8379	0.8385	0.8395	0.8379
0.1523	8.0	2280	0.7268	0.8439	0.8442	0.8455	0.8439
0.0928	9.0	2565	0.7364	0.8439	0.8452	0.8494	0.8439
0.0928	10.0	2850	0.7975	0.8478	0.8476	0.8476	0.8478
0.054	11.0	3135	0.9019	0.8498	0.8509	0.8554	0.8498
0.054	12.0	3420	0.8779	0.8538	0.8548	0.8578	0.8538
0.036	13.0	3705	0.8914	0.8617	0.8626	0.8652	0.8617
0.036	14.0	3990	0.8976	0.8538	0.8547	0.8572	0.8538
0.0232	15.0	4275	0.8993	0.8557	0.8563	0.8576	0.8557

Framework versions

Transformers 4.18.0
Pytorch 1.11.0+cu113
Datasets 2.1.0
Tokenizers 0.12.1