metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- financial_phrasebank
metrics:
- recall
- accuracy
- precision
base_model: deepmind/language-perceiver
model-index:
- name: TOMFINSEN
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: financial_phrasebank
type: financial_phrasebank
args: sentences_50agree
metrics:
- type: recall
value: 0.8985861629736692
name: Recall
- type: accuracy
value: 0.8742268041237113
name: Accuracy
- type: precision
value: 0.8509995913451198
name: Precision
TOMFINSEN
This model is a fine-tuned version of deepmind/language-perceiver on the financial_phrasebank dataset. It achieves the following results on the evaluation set:
- Loss: 0.3642
- Recall: 0.8986
- Accuracy: 0.8742
- Precision: 0.8510
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
- distributed_type: tpu
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Recall | Accuracy | Precision |
|---|---|---|---|---|---|---|
| 0.5403 | 1.0 | 273 | 0.4207 | 0.8358 | 0.8619 | 0.8534 |
| 0.3939 | 2.0 | 546 | 0.3750 | 0.8943 | 0.8577 | 0.8225 |
| 0.1993 | 3.0 | 819 | 0.3113 | 0.8882 | 0.8660 | 0.8367 |
| 0.301 | 4.0 | 1092 | 0.3642 | 0.8986 | 0.8742 | 0.8510 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.9.0+cu102
- Datasets 1.17.0
- Tokenizers 0.10.3