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---
license: apache-2.0
base_model: t5-large
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: t5-large_rte_sp0_ar0
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: rte
split: validation
args: rte
metrics:
- name: Accuracy
type: accuracy
value: 0.859375
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-large_rte_sp0_ar0
This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5699
- Accuracy: 0.8594
## 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: 16
- eval_batch_size: 32
- seed: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 750
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6946 | 0.27 | 25 | 0.6855 | 0.5271 |
| 0.6855 | 0.54 | 50 | 0.6477 | 0.6354 |
| 0.5931 | 0.82 | 75 | 0.4711 | 0.7942 |
| 0.4206 | 1.09 | 100 | 0.5129 | 0.8159 |
| 0.4076 | 1.36 | 125 | 0.4682 | 0.8375 |
| 0.2787 | 1.63 | 150 | 0.4392 | 0.8484 |
| 0.2772 | 1.9 | 175 | 0.4809 | 0.8520 |
| 0.2214 | 2.17 | 200 | 0.8655 | 0.8448 |
| 0.1505 | 2.45 | 225 | 0.9392 | 0.8628 |
| 0.1502 | 2.72 | 250 | 1.2747 | 0.8664 |
| 0.1149 | 2.99 | 275 | 3.4780 | 0.8448 |
| 0.1074 | 3.26 | 300 | 2.8125 | 0.8484 |
| 0.1359 | 3.53 | 325 | 3.0765 | 0.8448 |
| 0.0577 | 3.8 | 350 | 3.1358 | 0.8592 |
| 0.0212 | 4.08 | 375 | 3.3075 | 0.8520 |
| 0.0251 | 4.35 | 400 | 5.9088 | 0.8736 |
| 0.0532 | 4.62 | 425 | 5.5508 | 0.8700 |
| 0.0229 | 4.89 | 450 | 4.6194 | 0.8700 |
| 0.0517 | 5.16 | 475 | 3.2927 | 0.8592 |
| 0.0182 | 5.43 | 500 | 4.5065 | 0.8773 |
| 0.2538 | 5.71 | 525 | 4.5460 | 0.8809 |
| 0.0162 | 5.98 | 550 | 4.2678 | 0.8700 |
| 0.0221 | 6.25 | 575 | 4.6268 | 0.8664 |
| 0.007 | 6.52 | 600 | 4.3411 | 0.8664 |
| 0.0038 | 6.79 | 625 | 5.0136 | 0.8664 |
| 0.036 | 7.07 | 650 | 5.6308 | 0.8736 |
| 0.0064 | 7.34 | 675 | 5.9644 | 0.8736 |
| 0.0037 | 7.61 | 700 | 5.3223 | 0.8736 |
| 0.0121 | 7.88 | 725 | 5.3345 | 0.8736 |
| 0.0251 | 8.15 | 750 | 4.9899 | 0.8736 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.9.0
- Tokenizers 0.14.1
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