Instructions to use Firmansyah-Ibrahim/mt5_base-silver-standard-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Firmansyah-Ibrahim/mt5_base-silver-standard-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/mt5-base") model = PeftModel.from_pretrained(base_model, "Firmansyah-Ibrahim/mt5_base-silver-standard-lora") - Transformers
How to use Firmansyah-Ibrahim/mt5_base-silver-standard-lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Firmansyah-Ibrahim/mt5_base-silver-standard-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model final selesai dilatih dengan LoRA untuk mt5_base
Browse files
README.md
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.0014
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- Rouge1: 37.
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- Rouge2: 22.
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- Rougel: 36.
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- Rougelsum:
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
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| 35.0066 | 1.0 | 149 | 3.0369 | 15.
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| 12.4424 | 2.0 | 298 | 2.0791 | 33.
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| 11.1139 | 3.0 | 447 | 2.0014 | 37.
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### Framework versions
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.0014
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- Rouge1: 37.7941
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- Rouge2: 22.0953
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- Rougel: 36.8509
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- Rougelsum: 36.9714
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
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| 35.0066 | 1.0 | 149 | 3.0369 | 15.5109 | 5.2653 | 15.0068 | 15.042 |
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| 12.4424 | 2.0 | 298 | 2.0791 | 33.6692 | 19.2782 | 32.7224 | 32.7674 |
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| 11.1139 | 3.0 | 447 | 2.0014 | 37.7941 | 22.0953 | 36.8509 | 36.9714 |
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### Framework versions
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