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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_cola_dense_sp0_ar0
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: cola
split: validation
args: cola
metrics:
- name: Accuracy
type: accuracy
value: 0.0
---
<!-- 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_cola_dense_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: 4.7611
- Accuracy: 0.0
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6121 | 0.05 | 25 | 0.6257 | 0.6913 |
| 0.4507 | 0.09 | 50 | 0.6018 | 0.6913 |
| 0.2862 | 0.14 | 75 | 0.5646 | 0.8006 |
| 0.5917 | 0.19 | 100 | 0.5203 | 0.7929 |
| 0.3317 | 0.23 | 125 | 0.4479 | 0.8236 |
| 0.3637 | 0.28 | 150 | 0.4355 | 0.8245 |
| 0.2844 | 0.33 | 175 | 0.5032 | 0.8245 |
| 0.3406 | 0.37 | 200 | 0.5102 | 0.8121 |
| 0.4321 | 0.42 | 225 | 0.4290 | 0.8150 |
| 0.5212 | 0.47 | 250 | 0.4134 | 0.8293 |
| 0.4152 | 0.51 | 275 | 0.5055 | 0.8207 |
| 0.453 | 0.56 | 300 | 0.3974 | 0.8265 |
| 0.3412 | 0.61 | 325 | 0.4409 | 0.8245 |
| 0.3251 | 0.65 | 350 | 0.4538 | 0.8255 |
| 0.3255 | 0.7 | 375 | 0.3817 | 0.8313 |
| 0.2671 | 0.75 | 400 | 0.4162 | 0.8255 |
| 0.3995 | 0.79 | 425 | 0.4150 | 0.8303 |
| 0.4005 | 0.84 | 450 | 0.4125 | 0.8303 |
| 0.2897 | 0.89 | 475 | 0.4895 | 0.8226 |
| 0.4079 | 0.93 | 500 | 0.4064 | 0.8351 |
| 0.2597 | 0.98 | 525 | 0.6631 | 0.8447 |
| 0.2189 | 1.03 | 550 | 0.5056 | 0.8236 |
| 0.329 | 1.07 | 575 | 6.1282 | 0.8284 |
| 0.44 | 1.12 | 600 | 0.5057 | 0.8380 |
| 0.164 | 1.17 | 625 | 0.5032 | 0.8313 |
| 0.2996 | 1.21 | 650 | 0.9884 | 0.8341 |
| 0.2425 | 1.26 | 675 | 0.5208 | 0.8418 |
| 0.1987 | 1.31 | 700 | 0.4573 | 0.8389 |
| 0.1581 | 1.36 | 725 | 1.1812 | 0.8150 |
| 0.4067 | 1.4 | 750 | 0.6437 | 0.8293 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.11.6
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