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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_sst2_sp0_ar0
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: sst2
split: validation
args: sst2
metrics:
- name: Accuracy
type: accuracy
value: 0.9560546875
---
<!-- 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_sst2_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: 0.3456
- Accuracy: 0.9561
## 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
- distributed_type: tpu
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6852 | 0.01 | 25 | 0.6952 | 0.5092 |
| 0.6751 | 0.01 | 50 | 0.6331 | 0.7546 |
| 0.603 | 0.02 | 75 | 0.4811 | 0.8899 |
| 0.3459 | 0.02 | 100 | 0.2048 | 0.9335 |
| 0.1808 | 0.03 | 125 | 0.2377 | 0.9300 |
| 0.1933 | 0.04 | 150 | 0.3369 | 0.9323 |
| 0.527 | 0.04 | 175 | 0.6582 | 0.9404 |
| 0.2241 | 0.05 | 200 | 0.1874 | 0.9507 |
| 0.1997 | 0.05 | 225 | 0.5160 | 0.9472 |
| 0.2192 | 0.06 | 250 | 0.5193 | 0.9461 |
| 0.168 | 0.07 | 275 | 0.4091 | 0.9484 |
| 0.1879 | 0.07 | 300 | 0.3114 | 0.9427 |
| 0.1653 | 0.08 | 325 | 0.5526 | 0.9484 |
| 0.1847 | 0.08 | 350 | 0.6536 | 0.9450 |
| 0.1449 | 0.09 | 375 | 0.6520 | 0.9438 |
| 0.2485 | 0.1 | 400 | 0.4093 | 0.9518 |
| 0.1604 | 0.1 | 425 | 0.2821 | 0.9461 |
| 0.1316 | 0.11 | 450 | 0.8609 | 0.9461 |
| 0.1754 | 0.11 | 475 | 0.4047 | 0.9472 |
| 0.1524 | 0.12 | 500 | 0.4034 | 0.9495 |
| 0.4571 | 0.13 | 525 | 0.2895 | 0.9495 |
| 0.1448 | 0.13 | 550 | 0.5239 | 0.9484 |
| 0.1459 | 0.14 | 575 | 0.2996 | 0.9518 |
| 0.2131 | 0.14 | 600 | 0.2983 | 0.9495 |
| 0.1298 | 0.15 | 625 | 0.5322 | 0.9484 |
| 0.1519 | 0.16 | 650 | 0.5311 | 0.9518 |
| 0.1809 | 0.16 | 675 | 0.5271 | 0.9495 |
| 0.1495 | 0.17 | 700 | 0.5282 | 0.9495 |
| 0.1665 | 0.17 | 725 | 0.5307 | 0.9507 |
| 0.1978 | 0.18 | 750 | 0.5295 | 0.9507 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.0+cu118
- Datasets 2.14.5
- Tokenizers 0.11.6
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