BLOOM_AAID_structured_train_final_last
This model is a fine-tuned version of bigscience/bloom-7b1 on the AAID_structured dataset. It achieves the following results on the evaluation set:
- Loss: 0.8413
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.817 | 0.2188 | 200 | 0.8413 |
0.381 | 0.4375 | 400 | 0.8806 |
0.3025 | 0.6563 | 600 | 1.0179 |
0.1879 | 0.8750 | 800 | 1.1555 |
0.0744 | 1.0938 | 1000 | 1.2785 |
0.0231 | 1.3126 | 1200 | 1.3369 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for Holmeister/BLOOM_AAID_structured_train_final_last
Base model
bigscience/bloom-7b1