metadata
language:
- en
base_model: google-t5/t5-base
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: RTE
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE RTE
type: glue
args: rte
metrics:
- name: Accuracy
type: accuracy
value: 0.6931407942238267
RTE
This model is a fine-tuned version of google-t5/t5-base on the GLUE RTE dataset. It achieves the following results on the evaluation set:
- Loss: 0.7698
- Accuracy: 0.6931
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 78 | 0.6982 | 0.4946 |
| No log | 2.0 | 156 | 0.6822 | 0.5632 |
| No log | 3.0 | 234 | 0.6642 | 0.5921 |
| No log | 4.0 | 312 | 0.6545 | 0.6101 |
| No log | 5.0 | 390 | 0.6433 | 0.6390 |
| No log | 6.0 | 468 | 0.6844 | 0.6606 |
| 0.5942 | 7.0 | 546 | 0.7054 | 0.6462 |
| 0.5942 | 8.0 | 624 | 0.7449 | 0.6643 |
| 0.5942 | 9.0 | 702 | 0.7662 | 0.6715 |
| 0.5942 | 10.0 | 780 | 0.7698 | 0.6931 |
Framework versions
- Transformers 4.43.3
- Pytorch 1.11.0+cu113
- Datasets 2.20.0
- Tokenizers 0.19.1