transformers pytorch t5 text-classification generated_from_trainer dataset:glue base_model:google-t5/t5-base base_model:finetune:google-t5/t5-base license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: t5-base
datasets:
- glue
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: t5-base_qnli_dense_epochs-8
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      config: qnli
      split: validation
      args: qnli
    metrics:
    - type: accuracy
      value: 0.9269632070291048
      name: Accuracy
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# t5-base_qnli_dense_epochs-8

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: 0.1982
- Accuracy: 0.9270

## 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: 64
- seed: 0
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6742        | 0.01  | 50   | 0.6559          | 0.5380   |
| 0.4309        | 0.02  | 100  | 0.4215          | 0.8433   |
| 0.4535        | 0.02  | 150  | 0.3441          | 0.8644   |
| 0.2523        | 0.03  | 200  | 0.2892          | 0.8957   |
| 0.2616        | 0.04  | 250  | 0.2927          | 0.8986   |
| 0.2088        | 0.05  | 300  | 0.3608          | 0.8796   |
| 0.2454        | 0.05  | 350  | 0.2730          | 0.9087   |
| 0.2824        | 0.06  | 400  | 0.2819          | 0.8900   |
| 0.308         | 0.07  | 450  | 0.2904          | 0.8966   |
| 0.2035        | 0.08  | 500  | 0.3073          | 0.8951   |
| 0.2096        | 0.08  | 550  | 0.2743          | 0.9061   |
| 0.338         | 0.09  | 600  | 0.2520          | 0.9072   |
| 0.2484        | 0.1   | 650  | 0.2702          | 0.9030   |
| 0.2042        | 0.11  | 700  | 0.2476          | 0.9138   |
| 0.2908        | 0.11  | 750  | 0.2194          | 0.9180   |
| 0.1985        | 0.12  | 800  | 0.2432          | 0.9169   |
| 0.19          | 0.13  | 850  | 0.2615          | 0.9112   |
| 0.2186        | 0.14  | 900  | 0.2289          | 0.9215   |
| 0.2208        | 0.15  | 950  | 0.2272          | 0.9204   |
| 0.3049        | 0.15  | 1000 | 0.3508          | 0.8880   |
| 0.3373        | 0.16  | 1050 | 0.2363          | 0.9105   |
| 0.2493        | 0.17  | 1100 | 0.2196          | 0.9206   |
| 0.2359        | 0.18  | 1150 | 0.2160          | 0.9237   |
| 0.2207        | 0.18  | 1200 | 0.2211          | 0.9217   |
| 0.2824        | 0.19  | 1250 | 0.2386          | 0.9182   |
| 0.3605        | 0.2   | 1300 | 0.2548          | 0.9112   |
| 0.2763        | 0.21  | 1350 | 0.2579          | 0.9149   |
| 0.2299        | 0.21  | 1400 | 0.2104          | 0.9226   |
| 0.1787        | 0.22  | 1450 | 0.2280          | 0.9224   |
| 0.1961        | 0.23  | 1500 | 0.2244          | 0.9233   |
| 0.1923        | 0.24  | 1550 | 0.2245          | 0.9231   |
| 0.1844        | 0.24  | 1600 | 0.2735          | 0.9123   |
| 0.1714        | 0.25  | 1650 | 0.3108          | 0.9121   |
| 0.2606        | 0.26  | 1700 | 0.2238          | 0.9189   |
| 0.3326        | 0.27  | 1750 | 0.2363          | 0.9132   |
| 0.1379        | 0.27  | 1800 | 0.2429          | 0.9094   |
| 0.2266        | 0.28  | 1850 | 0.2416          | 0.9224   |
| 0.2654        | 0.29  | 1900 | 0.2277          | 0.9242   |
| 0.6668        | 0.3   | 1950 | 0.2808          | 0.9092   |
| 0.1875        | 0.31  | 2000 | 0.1982          | 0.9270   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.9.0
- Tokenizers 0.14.1
