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IndicBART_new_2 – AI Model by october-sd | AlphaNeural AI
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IndicBART_new_2
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transformers
tensorboard
safetensors
mbart
text2text-generation
summarization
generated_from_trainer
ai4bharat/IndicBART
finetune
endpoints_compatible
us
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IndicBART_new_2
This model is a fine-tuned version of
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