End of training

README.md

@@ -0,0 +1,76 @@
+---
+license: mit
+base_model: naver-clova-ix/donut-base
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- bleu
+- wer
+model-index:
+- name: donut-base-sroie-test-050824
+  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. -->
+
+# donut-base-sroie-test-050824
+
+This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5823
+- Bleu: 0.0595
+- Precisions: [0.7332123411978222, 0.6290983606557377, 0.5741176470588235, 0.5248618784530387]
+- Brevity Penalty: 0.0974
+- Length Ratio: 0.3004
+- Translation Length: 551
+- Reference Length: 1834
+- Cer: 0.7739
+- Wer: 0.8665
+
+## 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: 2e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 2
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Bleu   | Precisions                                                                            | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Cer    | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|
+| 3.716         | 1.0   | 250  | 1.7346          | 0.0080 | [0.3276089828269485, 0.05475504322766571, 0.01901743264659271, 0.0035211267605633804] | 0.2411          | 0.4128       | 757                | 1834             | 0.8647 | 0.9639 |
+| 1.3396        | 2.0   | 500  | 0.8150          | 0.0346 | [0.6405353728489483, 0.46304347826086956, 0.3702770780856423, 0.2964071856287425]     | 0.0815          | 0.2852       | 523                | 1834             | 0.7877 | 0.8990 |
+| 0.8804        | 3.0   | 750  | 0.6424          | 0.0586 | [0.7463235294117647, 0.6486486486486487, 0.5933014354066986, 0.5408450704225352]      | 0.0934          | 0.2966       | 544                | 1834             | 0.7674 | 0.8638 |
+| 0.6436        | 4.0   | 1000 | 0.5823          | 0.0595 | [0.7332123411978222, 0.6290983606557377, 0.5741176470588235, 0.5248618784530387]      | 0.0974          | 0.3004       | 551                | 1834             | 0.7739 | 0.8665 |
+
+
+### Framework versions
+
+- Transformers 4.41.0.dev0
+- Pytorch 2.1.0
+- Datasets 2.19.1
+- Tokenizers 0.19.1

added_tokens.json

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+  "<s_synthdog>": 57524,
+  "<s_total>": 57525,
+  "<sep/>": 57522
+}

generation_config.json

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+{
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+  "eos_token_id": 2,
+  "forced_eos_token_id": 2,
+  "pad_token_id": 1,
+  "transformers_version": "4.41.0.dev0"
+}

model.safetensors

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preprocessor_config.json

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+    "images",
+    "do_resize",
+    "size",
+    "resample",
+    "do_thumbnail",
+    "do_align_long_axis",
+    "do_pad",
+    "random_padding",
+    "do_rescale",
+    "rescale_factor",
+    "do_normalize",
+    "image_mean",
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+  "image_processor_type": "DonutImageProcessor",
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+  "processor_class": "DonutProcessor",
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": [
+    720,
+    960
+  ]
+}

runs/May08_13-47-11_ip-172-16-185-56.ec2.internal/events.out.tfevents.1715176032.ip-172-16-185-56.ec2.internal.9548.1

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sentencepiece.bpe.model

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special_tokens_map.json

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tokenizer_config.json

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+}