webnlg-challenge/web_nlg
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How to use milyiyo/stog-t5-small with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("milyiyo/stog-t5-small")
model = AutoModelForSeq2SeqLM.from_pretrained("milyiyo/stog-t5-small")This model is a fine-tuned version of t5-small on the web_nlg 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 |
|---|---|---|---|
| No log | 0.12 | 100 | 0.4625 |
| No log | 0.24 | 200 | 0.3056 |
| No log | 0.36 | 300 | 0.2393 |
| No log | 0.48 | 400 | 0.1999 |
| No log | 0.61 | 500 | 0.1740 |
| No log | 0.73 | 600 | 0.1562 |
| No log | 0.85 | 700 | 0.1467 |
| No log | 0.97 | 800 | 0.1418 |