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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- gsm8k
model-index:
- name: flan-t5-large-finetuned-gsm8k
results: []
widget:
- text: "Please, answer the following question reasoning step-by-step:
If Manu eats twice a day, how many meals does he take for a week?"
- text: "Please, answer the following question reasoning step-by-step: Manu bought 4 apples and lost one in the market. How many apples does Manu have?"
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# flan-t5-large-finetuned-gsm8k
This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/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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