esdurmus/wiki_lingua
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How to use eslamxm/AraT5v2-base-1024-finetuned-ar-wikilingua with Transformers:
# 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="eslamxm/AraT5v2-base-1024-finetuned-ar-wikilingua") # Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("eslamxm/AraT5v2-base-1024-finetuned-ar-wikilingua")
model = AutoModelForSeq2SeqLM.from_pretrained("eslamxm/AraT5v2-base-1024-finetuned-ar-wikilingua")This model is a fine-tuned version of UBC-NLP/AraT5v2-base-1024 on the wiki_lingua dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
|---|---|---|---|---|---|---|---|---|
| 5.2884 | 1.0 | 4998 | 4.4307 | 23.0 | 8.16 | 20.56 | 17.66 | 70.77 |
| 4.6798 | 2.0 | 9996 | 4.2972 | 24.48 | 8.95 | 21.86 | 17.57 | 71.56 |
| 4.4355 | 3.0 | 14994 | 4.2313 | 24.85 | 9.17 | 22.23 | 17.68 | 71.7 |
| 4.2772 | 4.0 | 19992 | 4.1972 | 25.41 | 9.5 | 22.65 | 17.63 | 72.08 |
| 4.1551 | 5.0 | 24990 | 4.1724 | 25.43 | 9.44 | 22.58 | 17.68 | 72.08 |
| 4.0604 | 6.0 | 29988 | 4.1626 | 25.44 | 9.56 | 22.67 | 17.52 | 72.19 |
| 3.989 | 7.0 | 34986 | 4.1616 | 25.71 | 9.68 | 22.91 | 17.71 | 72.29 |
| 3.9467 | 8.0 | 39984 | 4.1591 | 25.81 | 9.81 | 23.03 | 17.67 | 72.33 |
Base model
UBC-NLP/AraT5v2-base-1024