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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_epochs-7_decoder_all_sparsity10
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: 0.837967401725791
---
<!-- 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_epochs-7_decoder_all_sparsity10
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: 4.6969
- Accuracy: 0.8380
## 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: 64
- eval_batch_size: 128
- seed: 1
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 7
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5441 | 0.37 | 25 | 0.5813 | 0.6913 |
| 0.3969 | 0.75 | 50 | 0.5219 | 0.8044 |
| 0.3537 | 1.12 | 75 | 0.4713 | 0.8313 |
| 0.2905 | 1.49 | 100 | 0.6308 | 0.8150 |
| 0.3157 | 1.87 | 125 | 0.4301 | 0.8341 |
| 0.2208 | 2.24 | 150 | 2.3147 | 0.8332 |
| 0.2231 | 2.61 | 175 | 0.4612 | 0.8341 |
| 0.2404 | 2.99 | 200 | 1.5471 | 0.8265 |
| 0.1697 | 3.36 | 225 | 0.8701 | 0.8313 |
| 0.131 | 3.73 | 250 | 1.2642 | 0.8380 |
| 0.1219 | 4.1 | 275 | 0.9926 | 0.8370 |
| 0.2647 | 4.48 | 300 | 5.1919 | 0.8341 |
| 0.1329 | 4.85 | 325 | 2.2726 | 0.8418 |
| 0.0857 | 5.22 | 350 | 4.2193 | 0.8370 |
| 0.0989 | 5.6 | 375 | 5.3604 | 0.8389 |
| 0.2557 | 5.97 | 400 | 3.0246 | 0.8341 |
| 0.2617 | 6.34 | 425 | 5.6630 | 0.8456 |
| 0.2526 | 6.72 | 450 | 6.0474 | 0.8360 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.9.0
- Tokenizers 0.14.1
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