File size: 2,145 Bytes
cbad5f3 9839730 cbad5f3 9839730 cbad5f3 9839730 cbad5f3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
---
license: bsd-3-clause
base_model: Salesforce/codet5p-220m
tags:
- generated_from_trainer
model-index:
- name: SolExplain
results: []
---
<!-- 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. -->
# SolExplain
This model is a fine-tuned version of [Salesforce/codet5p-220m](https://huggingface.co/Salesforce/codet5p-220m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2952
## 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: 0.0001
- train_batch_size: 10
- eval_batch_size: 10
- seed: 100
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 40
- total_eval_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 0.658 | 1.0 | 19184 | 0.5830 |
| 0.5403 | 2.0 | 38368 | 0.4988 |
| 0.48 | 3.0 | 57552 | 0.4473 |
| 0.4282 | 4.0 | 76736 | 0.4124 |
| 0.3918 | 5.0 | 95920 | 0.3857 |
| 0.3464 | 6.0 | 115104 | 0.3650 |
| 0.3222 | 7.0 | 134288 | 0.3503 |
| 0.3007 | 8.0 | 153472 | 0.3357 |
| 0.2782 | 9.0 | 172656 | 0.3269 |
| 0.2562 | 10.0 | 191840 | 0.3184 |
| 0.2386 | 11.0 | 211024 | 0.3101 |
| 0.2196 | 12.0 | 230208 | 0.3020 |
| 0.2042 | 13.0 | 249392 | 0.3005 |
| 0.1931 | 14.0 | 268576 | 0.2971 |
| 0.1734 | 15.0 | 287760 | 0.2952 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.13.3
|