IndicBART_new_2 / README.md
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---
base_model: ai4bharat/IndicBART
tags:
- summarization
- generated_from_trainer
model-index:
- name: IndicBART_new_2
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. -->
# IndicBART_new_2
This model is a fine-tuned version of [ai4bharat/IndicBART](https://huggingface.co/ai4bharat/IndicBART) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3218
## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 0.96 | 11 | 5.4424 |
| No log | 2.0 | 23 | 4.3784 |
| No log | 2.96 | 34 | 4.0395 |
| No log | 4.0 | 46 | 3.7066 |
| No log | 4.96 | 57 | 3.5332 |
| No log | 6.0 | 69 | 3.4435 |
| No log | 6.96 | 80 | 3.3687 |
| No log | 7.65 | 88 | 3.3218 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.2