I am trying to fine-tune Mistral Large on our proprietary customer support transcripts, but the loss function is not converging, so what hyperparameters should I adjust?
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I am trying to fine-tune Mistral Large on our proprietary customer support transcripts, but the loss function is not converging, so what hyperparameters should I adjust?
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
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ChatGPT2 real searches · gpt-6
Mistral Large fine-tuning documentation learning rate batch size sequence length official Google ↗
Hugging Face TRL SFTTrainer loss not converging learning rate packing assistant only loss masking documentation Google ↗
- SFT Trainer · huggingface.co
- trl/docs/source/sft_trainer.md at main · huggingface/trl · github.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Mistral Large fine-tuning documentation learning rate batch size sequence length official OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
Hugging Face TRL SFTTrainer loss not converging learning rate packing assistant only loss masking documentation OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |