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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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datasets: |
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- opus100 |
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base_model: google/mt5-base |
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model-index: |
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- name: ft-t5-small-on-opus100 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ft-t5-small-on-opus100 |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the opus100 dataset. |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.001 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.15.1 |
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## Training procedure |
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The following `bitsandbytes` quantization config was used during training: |
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- quant_method: QuantizationMethod.BITS_AND_BYTES |
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- load_in_8bit: True |
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- load_in_4bit: False |
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- llm_int8_threshold: 6.0 |
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- llm_int8_skip_modules: None |
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- llm_int8_enable_fp32_cpu_offload: False |
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- llm_int8_has_fp16_weight: False |
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- bnb_4bit_quant_type: fp4 |
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- bnb_4bit_use_double_quant: False |
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- bnb_4bit_compute_dtype: float32 |
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### Framework versions |
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- PEFT 0.6.2.dev0 |
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