---
license: apache-2.0
base_model: google/t5-v1_1-large
tags:
- generated_from_trainer
model-index:
- name: SBIC-google-t5-v1_1-large-inter_model-frequency-model_annots_str
  results: []
---

<!-- 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. -->

# SBIC-google-t5-v1_1-large-inter_model-frequency-model_annots_str

This model is a fine-tuned version of [google/t5-v1_1-large](https://huggingface.co/google/t5-v1_1-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: nan

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 7.167         | 1.0   | 392  | 7.3219          |
| 5.9187        | 2.0   | 784  | 6.1190          |
| 0.454         | 3.0   | 1176 | 0.4329          |
| 0.4799        | 4.0   | 1568 | 0.4202          |
| 0.4521        | 5.0   | 1960 | 0.4199          |
| 0.4624        | 6.0   | 2352 | 0.4321          |
| 0.4301        | 7.0   | 2744 | 0.4406          |
| 0.4482        | 8.0   | 3136 | 0.4544          |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1