End of training

README.md

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+---
+library_name: peft
+license: apache-2.0
+base_model: HuggingFaceTB/SmolVLM-Base
+tags:
+- base_model:adapter:HuggingFaceTB/SmolVLM-Base
+- lora
+- transformers
+metrics:
+- wer
+model-index:
+- name: SmolVLM-Base-ocr-isl
+  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. -->
+
+# SmolVLM-Base-ocr-isl
+
+This model is a fine-tuned version of [HuggingFaceTB/SmolVLM-Base](https://huggingface.co/HuggingFaceTB/SmolVLM-Base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0420
+- Wer: 0.4108
+- Cer: 0.4556
+- Exact Match: 0.0
+- Special Char Acc: 0.0084
+- Seq Acc 5: 0.0
+- Seq Acc 10: 0.0
+
+## 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: 0.0001
+- train_batch_size: 4
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 50
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    | Exact Match | Special Char Acc | Seq Acc 5 | Seq Acc 10 |
+|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:-----------:|:----------------:|:---------:|:----------:|
+| 0.1564        | 0.1245 | 500  | 0.1101          | 0.4213 | 0.5448 | 0.0         | 0.0140           | 0.0       | 0.0        |
+| 0.0866        | 0.2490 | 1000 | 0.0791          | 0.3409 | 0.4947 | 0.0         | 0.0112           | 0.0       | 0.0        |
+| 0.1093        | 0.3735 | 1500 | 0.0646          | 0.4073 | 0.4989 | 0.0         | 0.0140           | 0.0       | 0.0        |
+| 0.1016        | 0.4979 | 2000 | 0.0570          | 0.3951 | 0.4507 | 0.0         | 0.0056           | 0.0       | 0.0        |
+| 0.1           | 0.6224 | 2500 | 0.0504          | 0.4318 | 0.5059 | 0.0         | 0.0169           | 0.0       | 0.0        |
+| 0.0777        | 0.7469 | 3000 | 0.0415          | 0.4248 | 0.4692 | 0.0         | 0.0140           | 0.0       | 0.0        |
+| 0.107         | 0.8714 | 3500 | 0.0427          | 0.4021 | 0.4732 | 0.0         | 0.0140           | 0.0       | 0.0        |
+| 0.1286        | 0.9959 | 4000 | 0.0420          | 0.4108 | 0.4556 | 0.0         | 0.0084           | 0.0       | 0.0        |
+
+
+### Framework versions
+
+- PEFT 0.17.1
+- Transformers 4.56.2
+- Pytorch 2.8.0+cu128
+- Datasets 4.1.0
+- Tokenizers 0.22.1

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": {
+    "base_model_class": "Idefics3ForConditionalGeneration",
+    "parent_library": "transformers.models.idefics3.modeling_idefics3"
+  },
+  "base_model_name_or_path": "HuggingFaceTB/SmolVLM-Base",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": "gaussian",
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 8,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "up_proj",
+    "down_proj",
+    "gate_proj",
+    "k_proj",
+    "o_proj",
+    "v_proj"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": true,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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training_args.bin

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