mt5-small-finetuned-13f-reports

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mt5-small-finetuned-13f-reports

This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.4818
• Rouge1: 0.3235
• Rouge2: 0.2725
• Rougel: 0.3146
• Rougelsum: 0.3161

Model description

More information needed

Intended uses & limitations

The model was fine tuned on a dataset of 1000+ quarterly 13F reports. It is intended for use with automating the generation of summaries of articles before they are published. This allows you to put in a TL;DR summary without having to write one on your own.

NOTE: The HuggingFace hosted Inference API interface takes the default parameters and so only outputs about 20 words of text. To get a full summary, use the Inference API directly and pass in max_length=120 or so.

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5.6e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 8

Training results

Framework versions

• Transformers 4.34.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.14.0