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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: 0.9453125
---
<!-- 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: 0.1944
- Accuracy: 0.9453
## 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
- num_epochs: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6815 | 0.01 | 25 | 0.6999 | 0.5092 |
| 0.6592 | 0.01 | 50 | 0.6221 | 0.6445 |
| 0.5832 | 0.02 | 75 | 0.4570 | 0.7993 |
| 0.2882 | 0.02 | 100 | 0.2076 | 0.9358 |
| 0.1894 | 0.03 | 125 | 0.3499 | 0.9404 |
| 0.1864 | 0.04 | 150 | 0.2963 | 0.9461 |
| 0.2553 | 0.04 | 175 | 0.6929 | 0.9289 |
| 0.245 | 0.05 | 200 | 0.4761 | 0.9323 |
| 0.2042 | 0.05 | 225 | 0.5294 | 0.9461 |
| 0.2002 | 0.06 | 250 | 0.8441 | 0.9472 |
| 0.1633 | 0.07 | 275 | 0.8560 | 0.9495 |
| 0.1939 | 0.07 | 300 | 0.3197 | 0.9450 |
| 0.1928 | 0.08 | 325 | 0.4214 | 0.9472 |
| 0.2201 | 0.08 | 350 | 0.5266 | 0.9484 |
| 0.143 | 0.09 | 375 | 0.8642 | 0.9450 |
| 0.2354 | 0.1 | 400 | 1.2116 | 0.9335 |
| 0.1692 | 0.1 | 425 | 0.1807 | 0.9472 |
| 0.1531 | 0.11 | 450 | 0.6431 | 0.9484 |
| 0.152 | 0.11 | 475 | 1.4046 | 0.9553 |
| 0.1948 | 0.12 | 500 | 0.1596 | 0.9553 |
| 0.2007 | 0.13 | 525 | 0.1779 | 0.9438 |
| 0.1338 | 0.13 | 550 | 0.6476 | 0.9495 |
| 0.3812 | 0.14 | 575 | 0.3901 | 0.9484 |
| 0.7052 | 0.14 | 600 | 0.1740 | 0.9507 |
| 0.8601 | 0.15 | 625 | 1.5226 | 0.9484 |
| 1.384 | 0.16 | 650 | 0.6605 | 0.9427 |
| 0.6833 | 0.16 | 675 | 0.7313 | 0.9484 |
| 0.1833 | 0.17 | 700 | 0.4110 | 0.9438 |
| 0.1968 | 0.17 | 725 | 0.2914 | 0.9450 |
| 0.2001 | 0.18 | 750 | 0.1947 | 0.9335 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.11.6
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