flan-t5-large-finetuned-gsm8k
This model is a fine-tuned version of google/flan-t5-large on the gsm8k dataset. It achieves the following results on the evaluation set:
- Loss: 0.3091
 - Rouge2 Precision: 0.4454
 - Rouge2 Recall: 0.0953
 - Rouge2 Fmeasure: 0.152
 
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: 5e-05
 - train_batch_size: 2
 - eval_batch_size: 4
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 4
 
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | 
|---|---|---|---|---|---|---|
| 0.34 | 1.0 | 3737 | 0.3206 | 0.4241 | 0.089 | 0.1423 | 
| 0.2786 | 2.0 | 7474 | 0.3089 | 0.4334 | 0.0916 | 0.1463 | 
| 0.247 | 3.0 | 11211 | 0.3074 | 0.4461 | 0.095 | 0.1515 | 
| 0.2283 | 4.0 | 14948 | 0.3091 | 0.4454 | 0.0953 | 0.152 | 
Framework versions
- Transformers 4.24.0
 - Pytorch 1.12.1+cu113
 - Datasets 2.6.1
 - Tokenizers 0.13.2
 
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