Model save

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
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+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,55 @@
+---
+library_name: peft
+license: apache-2.0
+base_model: google/madlad400-3b-mt
+tags:
+- base_model:adapter:google/madlad400-3b-mt
+- lora
+- transformers
+model-index:
+- name: madlad-bm-fr
+  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. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/bamalingua-bamalingua/Bamalingua-madlat/runs/mnejoedh)
+# madlad-bm-fr
+
+This model is a fine-tuned version of [google/madlad400-3b-mt](https://huggingface.co/google/madlad400-3b-mt) on an unknown dataset.
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- training_steps: 40
+
+### Framework versions
+
+- PEFT 0.17.1
+- Transformers 4.57.1
+- Pytorch 2.8.0+cu126
+- Datasets 4.4.2
+- Tokenizers 0.22.1

adapter_config.json

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+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
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+  "peft_type": "LORA",
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+  "r": 16,
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+  "target_modules": [
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+    "k",
+    "wi_0",
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+  ],
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+  "task_type": "SEQ_2_SEQ_LM",
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+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

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special_tokens_map.json

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tokenizer_config.json

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training_args.bin

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