js0309/lab1_random

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: Helsinki-NLP/opus-mt-en-fr
+tags:
+- generated_from_trainer
+datasets:
+- kde4
+metrics:
+- bleu
+model-index:
+- name: lab1_random
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: kde4
+      type: kde4
+      config: en-fr
+      split: train
+      args: en-fr
+    metrics:
+    - name: Bleu
+      type: bleu
+      value: 6.718448903517599
+---
+
+<!-- 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. -->
+
+# lab1_random
+
+This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-fr](https://huggingface.co/Helsinki-NLP/opus-mt-en-fr) on the kde4 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 5.2499
+- Model Preparation Time: 0.0031
+- Bleu: 6.7184
+
+## 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: 16
+- eval_batch_size: 32
+- seed: 42
+- 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: 5000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.57.6
+- Pytorch 2.10.0+cu128
+- Datasets 3.6.0
+- Tokenizers 0.22.2