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stefanbschneider/led-base-16384-lfqa
led-base-16384-lfqa is a machine learning model from stefanbschneider. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
This model is a fine-tuned version of stefanbschneider/led-base-16384-lfqa-ans-len-512 on an unknown dataset. It achieves the following results on the evaluation set:
More information needed
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More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Rouge2 | Task |
|---|---|---|---|---|---|
| 3.4849 | 0.0395 | 2000 | 3.4233 | 0.0387 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.4744 | 0.0789 | 4000 | 3.4411 | 0.0398 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.4919 | 0.1184 | 6000 | 3.4251 | 0.0378 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.487 | 0.1578 | 8000 | 3.4200 | 0.0397 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.4443 | 0.1973 | 10000 | 3.3870 | 0.0376 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.4597 | 0.2367 | 12000 | 3.3914 | 0.0405 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.4525 | 0.2762 | 14000 | 3.3845 | 0.0398 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.4618 | 0.3156 | 16000 | 3.3752 | 0.0424 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.4573 | 0.3551 | 18000 | 3.3693 | 0.0421 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.4164 | 0.3945 | 20000 | 3.3640 | 0.042 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.4125 | 0.4340 | 22000 | 3.3544 | 0.0412 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.3828 | 0.4734 | 24000 | 3.3423 | 0.0409 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.3965 | 0.5129 | 26000 | 3.3436 | 0.0416 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.3993 | 0.5524 | 28000 | 3.3339 | 0.0384 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.3909 | 0.5918 | 30000 | 3.3122 | 0.0414 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.3745 | 0.6313 | 32000 | 3.3158 | 0.0416 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.3665 | 0.6707 | 34000 | 3.3038 | 0.0424 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.3351 | 0.7102 | 36000 | 3.2915 | 0.0435 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.3629 | 0.7496 | 38000 | 3.2955 | 0.0436 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.3465 | 0.7891 | 40000 | 3.2888 | 0.0395 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.3127 | 0.8285 | 42000 | 3.2800 | 0.0414 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.3385 | 0.8680 | 44000 | 3.2767 | 0.0413 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.2882 | 0.9074 | 46000 | 3.2685 | 0.0437 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.3162 | 0.9469 | 48000 | 3.2639 | 0.0412 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |
| 3.3072 | 0.9863 | 50000 | 3.2615 | 0.0416 | {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'} |