ccdv/arxiv-summarization
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How to use WasibMehmood/TextSummizer with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("WasibMehmood/TextSummizer")
model = AutoModelForSeq2SeqLM.from_pretrained("WasibMehmood/TextSummizer")This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on an unknown 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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Generated Length |
|---|---|---|---|---|---|---|---|---|
| 3.0367 | 1.0 | 609 | 2.7608 | 0.4091 | 0.1389 | 0.2423 | 0.3401 | 122.0861 |
| 2.6396 | 2.0 | 1218 | 2.6925 | 0.4206 | 0.1468 | 0.2485 | 0.3508 | 124.4791 |
| 2.4229 | 3.0 | 1827 | 2.6837 | 0.421 | 0.1462 | 0.248 | 0.3488 | 120.0345 |
Base model
sshleifer/distilbart-cnn-12-6