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update model card README.md

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  ---
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- library_name: peft
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Training procedure
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- The following `bitsandbytes` quantization config was used during training:
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- - load_in_8bit: False
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- - load_in_4bit: True
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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: nf4
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- - bnb_4bit_use_double_quant: True
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- - bnb_4bit_compute_dtype: bfloat16
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- ### Framework versions
 
 
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- - PEFT 0.4.0
 
 
 
 
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  ---
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+ license: apache-2.0
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+ base_model: DAMO-NLP-MT/polylm-13b
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: polylm_13b_ft_alpaca_clean_dutch
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+ results: []
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  ---
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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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+
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+ # polylm_13b_ft_alpaca_clean_dutch
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+
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+ This model is a fine-tuned version of [DAMO-NLP-MT/polylm-13b](https://huggingface.co/DAMO-NLP-MT/polylm-13b) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.3355
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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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: 2e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 64
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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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+ - lr_scheduler_warmup_steps: 64
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+ - num_epochs: 2
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+
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+ ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.4311 | 0.16 | 128 | 1.4541 |
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+ | 1.3936 | 0.33 | 256 | 1.4141 |
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+ | 1.423 | 0.49 | 384 | 1.3960 |
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+ | 1.3672 | 0.66 | 512 | 1.3832 |
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+ | 1.3809 | 0.82 | 640 | 1.3754 |
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+ | 1.3581 | 0.99 | 768 | 1.3652 |
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+ | 1.3534 | 1.15 | 896 | 1.3599 |
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+ | 1.3334 | 1.32 | 1024 | 1.3535 |
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+ | 1.3351 | 1.48 | 1152 | 1.3475 |
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+ | 1.3178 | 1.65 | 1280 | 1.3411 |
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+ | 1.3341 | 1.81 | 1408 | 1.3378 |
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+ | 1.2976 | 1.98 | 1536 | 1.3355 |
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+
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+
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+ ### Framework versions
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+ - Transformers 4.31.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.0
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+ - Tokenizers 0.13.3