transformers tensorboard safetensors t5 text2text-generation generated_from_trainer summarization base_model:BeenaSamuel/t5_cnn_daily_mail_abstractive_summarizer_v2 base_model:finetune:BeenaSamuel/t5_cnn_daily_mail_abstractive_summarizer_v2 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: BeenaSamuel/t5_cnn_daily_mail_abstractive_summarizer_v2
pipeline_tag: summarization
tags:
- generated_from_trainer
model-index:
- name: multinews_cnn_logs
  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. -->

# multinews_cnn_logs

This model is a fine-tuned version of [BeenaSamuel/t5_cnn_daily_mail_abstractive_summarizer_v2](https://huggingface.co/BeenaSamuel/t5_cnn_daily_mail_abstractive_summarizer_v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.8039
- eval_rouge1: 0.5189
- eval_rouge2: 0.1941
- eval_rougeL: 0.397
- eval_gen_len: 311.236
- eval_runtime: 1446.5993
- eval_samples_per_second: 3.886
- eval_steps_per_second: 0.486
- epoch: 4.84
- step: 3400

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2