End of training

README.md

@@ -0,0 +1,73 @@
+---
+license: mit
+base_model: naver-clova-ix/donut-base
+tags:
+- generated_from_trainer
+metrics:
+- bleu
+- wer
+model-index:
+- name: donut_experiment_bayesian_trial_18
+  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_experiment_bayesian_trial_18
+
+This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5643
+- Bleu: 0.0698
+- Precisions: [0.8340248962655602, 0.7741176470588236, 0.7309782608695652, 0.6784565916398714]
+- Brevity Penalty: 0.0928
+- Length Ratio: 0.2961
+- Translation Length: 482
+- Reference Length: 1628
+- Cer: 0.7496
+- Wer: 0.8244
+
+## 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: 1.7803961202565393e-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: 3
+- 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    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|
+| 0.0287        | 1.0   | 253  | 0.5097          | 0.0722 | [0.8374485596707819, 0.7762237762237763, 0.7338709677419355, 0.6888888888888889] | 0.0954          | 0.2985       | 486                | 1628             | 0.7506 | 0.8208 |
+| 0.0159        | 2.0   | 506  | 0.5583          | 0.0697 | [0.8319502074688797, 0.7741176470588236, 0.7282608695652174, 0.6784565916398714] | 0.0928          | 0.2961       | 482                | 1628             | 0.7496 | 0.8232 |
+| 0.0118        | 3.0   | 759  | 0.5643          | 0.0698 | [0.8340248962655602, 0.7741176470588236, 0.7309782608695652, 0.6784565916398714] | 0.0928          | 0.2961       | 482                | 1628             | 0.7496 | 0.8244 |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.1.0
+- Datasets 2.18.0
+- Tokenizers 0.19.1

added_tokens.json

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+  "</s_company>": 57530,
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+}

generation_config.json

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+{
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "forced_eos_token_id": 2,
+  "pad_token_id": 1,
+  "transformers_version": "4.40.0"
+}

metrics.jsonl

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 {"eval_loss": 0.5097183585166931, "eval_bleu": 0.07222304930146295, "eval_precisions": [0.8374485596707819, 0.7762237762237763, 0.7338709677419355, 0.6888888888888889], "eval_brevity_penalty": 0.095388787518951, "eval_length_ratio": 0.2985257985257985, "eval_translation_length": 486, "eval_reference_length": 1628, "eval_cer": 0.750567601112786, "eval_wer": 0.8208277337195127, "eval_runtime": 70.7177, "eval_samples_per_second": 0.806, "eval_steps_per_second": 0.806, "epoch": 1.0}
 {"eval_loss": 0.5583482980728149, "eval_bleu": 0.06967912030432986, "eval_precisions": [0.8319502074688797, 0.7741176470588236, 0.7282608695652174, 0.6784565916398714], "eval_brevity_penalty": 0.09277358157754431, "eval_length_ratio": 0.29606879606879605, "eval_translation_length": 482, "eval_reference_length": 1628, "eval_cer": 0.7496114910201869, "eval_wer": 0.8231605622115609, "eval_runtime": 71.2858, "eval_samples_per_second": 0.8, "eval_steps_per_second": 0.8, "epoch": 2.0}
+{"eval_loss": 0.5643486976623535, "eval_bleu": 0.06978746944247413, "eval_precisions": [0.8340248962655602, 0.7741176470588236, 0.7309782608695652, 0.6784565916398714], "eval_brevity_penalty": 0.09277358157754431, "eval_length_ratio": 0.29606879606879605, "eval_translation_length": 482, "eval_reference_length": 1628, "eval_cer": 0.7496190716123485, "eval_wer": 0.8243788857983054, "eval_runtime": 71.1039, "eval_samples_per_second": 0.802, "eval_steps_per_second": 0.802, "epoch": 3.0}

model.safetensors

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preprocessor_config.json

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+    "resample",
+    "do_thumbnail",
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+}

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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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