How to use from the
Use from the
Transformers library
# Gated model: Login with a HF token with gated access permission
hf auth login
# Use a pipeline as a high-level helper
# Warning: Pipeline type "summarization" is no longer supported in transformers v5.
# You must load the model directly (see below) or downgrade to v4.x with:
# 'pip install "transformers<5.0.0'
from transformers import pipeline

pipe = pipeline("summarization", model="HooshvareLab/pn-summary-mt5-base")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("HooshvareLab/pn-summary-mt5-base")
model = AutoModelForSeq2SeqLM.from_pretrained("HooshvareLab/pn-summary-mt5-base")
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An mT5-base model on the pnSummary dataset to summarize articles.

Eval results

The following table summarizes the ROUGE scores obtained by the model for the validation set.

+-----------+------+-----------+--------+-----------+
|   Score   | Type | Precision | Recall | F-Measure |
+-----------+------+-----------+--------+-----------+
|   rouge1  | low  |   48.60   | 45.25  |   45.47   |
|   rouge1  | mid  |   49.22   | 45.79  |   46.02   |
|   rouge1  | high |   49.80   | 46.36  |   46.54   |
|           |      |           |        |           |
|    ***    | ***  |    ***    |  ***   |    ***    |
|           |      |           |        |           |
|   rouge2  | low  |   29.46   | 27.33  |   27.56   |
|   rouge2  | mid  |   30.08   | 27.93  |   28.12   |
|   rouge2  | high |   30.69   | 28.52  |   28.71   |
|           |      |           |        |           |
|    ***    | ***  |    ***    |  ***   |    ***    |
|           |      |           |        |           |
|   rougeL  | low  |   42.20   | 39.26  |   39.51   |
|   rougeL  | mid  |   42.80   | 39.86  |   40.07   |
|   rougeL  | high |   43.43   | 40.41  |   40.62   |
|           |      |           |        |           |
|    ***    | ***  |    ***    |  ***   |    ***    |
|           |      |           |        |           |
| rougeLsum | low  |   42.15   | 39.26  |   39.48   |
| rougeLsum | mid  |   42.82   | 39.87  |   40.09   |
| rougeLsum | high |   43.39   | 40.43  |   40.61   |
+-----------+------+-----------+--------+-----------+

Test results

The following table summarizes the ROUGE scores obtained by the model for the test set.

+-----------+------+-----------+--------+-----------+
|   Score   | Type | Precision | Recall | F-Measure |
+-----------+------+-----------+--------+-----------+
|   rouge1  | low  |   48.83   | 44.99  |   45.41   |
|   rouge1  | mid  |   49.39   | 45.52  |   45.91   |
|   rouge1  | high |   50.02   | 46.07  |   46.48   |
|           |      |           |        |           |
|    ***    | ***  |    ***    |  ***   |    ***    |
|           |      |           |        |           |
|   rouge2  | low  |   29.27   | 26.90  |   27.23   |
|   rouge2  | mid  |   29.97   | 27.52  |   27.84   |
|   rouge2  | high |   30.62   | 28.15  |   28.46   |
|           |      |           |        |           |
|    ***    | ***  |    ***    |  ***   |    ***    |
|           |      |           |        |           |
|   rougeL  | low  |   42.30   | 38.94  |   39.34   |
|   rougeL  | mid  |   42.85   | 39.54  |   39.90   |
|   rougeL  | high |   43.51   | 40.12  |   40.49   |
|           |      |           |        |           |
|    ***    | ***  |    ***    |  ***   |    ***    |
|           |      |           |        |           |
| rougeLsum | low  |   42.27   | 38.94  |   39.35   |
| rougeLsum | mid  |   42.86   | 39.53  |   39.90   |
| rougeLsum | high |   43.42   | 40.12  |   40.45   |
+-----------+------+-----------+--------+-----------+
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Dataset used to train HooshvareLab/pn-summary-mt5-base