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---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: t5-base_cola_moe_ex9_sp0_05_ar0_0_mare_mlp
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-base_cola_moe_ex9_sp0_05_ar0_0_mare_mlp
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9386
- 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: 32
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2328 | 0.09 | 25 | 1.1651 | 0.7383 |
| 0.764 | 0.19 | 50 | 0.7678 | 0.7287 |
| 0.6109 | 0.28 | 75 | 0.6739 | 0.7718 |
| 0.5633 | 0.37 | 100 | 0.5954 | 0.7661 |
| 0.5133 | 0.47 | 125 | 0.5870 | 0.7814 |
| 0.5224 | 0.56 | 150 | 0.5766 | 0.7785 |
| 0.4876 | 0.65 | 175 | 0.5574 | 0.7881 |
| 0.5157 | 0.75 | 200 | 0.5760 | 0.7881 |
| 0.4745 | 0.84 | 225 | 0.5327 | 0.7824 |
| 0.4612 | 0.93 | 250 | 0.5576 | 0.7900 |
| 0.4491 | 1.03 | 275 | 0.5174 | 0.7881 |
| 0.358 | 1.12 | 300 | 0.6065 | 0.7900 |
| 0.3363 | 1.21 | 325 | 0.6949 | 0.7919 |
| 0.4065 | 1.31 | 350 | 0.5112 | 0.7987 |
| 0.4044 | 1.4 | 375 | 0.5681 | 0.8063 |
| 0.3888 | 1.49 | 400 | 0.5422 | 0.7996 |
| 0.4992 | 1.59 | 425 | 0.5294 | 0.7900 |
| 0.4231 | 1.68 | 450 | 0.5221 | 0.8044 |
| 0.4912 | 1.77 | 475 | 0.4984 | 0.8130 |
| 0.4951 | 1.87 | 500 | 0.5109 | 0.8015 |
| 0.3117 | 1.96 | 525 | 0.5640 | 0.8044 |
| 0.3822 | 2.05 | 550 | 0.5524 | 0.8130 |
| 0.3886 | 2.15 | 575 | 0.6092 | 0.8121 |
| 0.305 | 2.24 | 600 | 0.5380 | 0.8111 |
| 0.4815 | 2.33 | 625 | 0.5478 | 0.8111 |
| 0.3298 | 2.43 | 650 | 0.5298 | 0.8150 |
| 0.3533 | 2.52 | 675 | 0.5043 | 0.8140 |
| 0.3706 | 2.61 | 700 | 0.5810 | 0.8178 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.11.6
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