transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:google/flan-t5-base base_model:finetune:google/flan-t5-base license:apache-2.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: google/flan-t5-base
license: apache-2.0
metrics:
- precision
- recall
- f1
tags:
- generated_from_trainer
model-index:
- name: flant5_offensive_translation_de_en_wmt
  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. -->

# flant5_offensive_translation_de_en_wmt

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0011
- Precision: 0.6551
- Recall: 0.5516
- F1: 0.5989
- Total Predictions: 3532

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Total Predictions |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:-----------------:|
| 0.3687        | 1.0   | 3003  | 0.0012          | 0.5471    | 0.5366 | 0.5418 | 3532              |
| 0.0166        | 2.0   | 6006  | 0.0011          | 0.6454    | 0.4542 | 0.5332 | 3532              |
| 0.0145        | 3.0   | 9009  | 0.0010          | 0.6111    | 0.6065 | 0.6088 | 3532              |
| 0.013         | 4.0   | 12012 | 0.0011          | 0.6904    | 0.4767 | 0.5640 | 3532              |
| 0.0121        | 5.0   | 15015 | 0.0011          | 0.6551    | 0.5516 | 0.5989 | 3532              |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.0.0+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
