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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_dense_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: 0.0
---
<!-- 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_rte_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: 0.9322
- 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: 8
- eval_batch_size: 16
- seed: 1
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6781 | 0.16 | 25 | 0.6834 | 0.5487 |
| 0.7041 | 0.32 | 50 | 0.6878 | 0.5523 |
| 0.689 | 0.48 | 75 | 0.6836 | 0.6065 |
| 0.6902 | 0.64 | 100 | 0.6630 | 0.5740 |
| 0.6458 | 0.8 | 125 | 0.5695 | 0.7112 |
| 0.5973 | 0.96 | 150 | 0.6138 | 0.6823 |
| 0.5697 | 1.12 | 175 | 0.5707 | 0.7581 |
| 0.4567 | 1.28 | 200 | 0.6558 | 0.7256 |
| 0.3796 | 1.44 | 225 | 0.4968 | 0.7870 |
| 0.3749 | 1.6 | 250 | 0.5082 | 0.8123 |
| 0.5187 | 1.76 | 275 | 0.4428 | 0.8123 |
| 0.4176 | 1.92 | 300 | 0.3940 | 0.8556 |
| 0.2678 | 2.08 | 325 | 0.4938 | 0.8484 |
| 0.0761 | 2.24 | 350 | 0.6533 | 0.8520 |
| 0.2082 | 2.4 | 375 | 0.5901 | 0.8484 |
| 0.4081 | 2.56 | 400 | 0.5939 | 0.8520 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.11.6
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