license: apache-2.0 | |
tags: | |
- summarization | |
- en | |
- mt5 | |
- Abstractive Summarization | |
- generated_from_trainer | |
datasets: | |
- cnn_dailymail | |
model-index: | |
- name: mt5-base-finetuned-en-cnn | |
results: [] | |
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# mt5-base-finetuned-en-cnn | |
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co./google/mt5-base) on the cnn_dailymail dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 3.1286 | |
- Rouge-1: 22.84 | |
- Rouge-2: 10.11 | |
- Rouge-l: 21.8 | |
- Gen Len: 19.0 | |
- Bertscore: 87.12 | |
## 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: 0.0005 | |
- train_batch_size: 4 | |
- eval_batch_size: 4 | |
- seed: 42 | |
- gradient_accumulation_steps: 8 | |
- total_train_batch_size: 32 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: linear | |
- lr_scheduler_warmup_steps: 250 | |
- num_epochs: 5 | |
- label_smoothing_factor: 0.1 | |
### Training results | |
### Framework versions | |
- Transformers 4.19.4 | |
- Pytorch 1.11.0+cu113 | |
- Datasets 2.2.2 | |
- Tokenizers 0.12.1 | |