Compute Metrics Huggingface Trainer. Here is the dimension of logits and labels that go into the compu

Here is the dimension of logits and labels that go into the compute_metrics function (50, 256, 50272) (total_records,seq_len_vocab_size). Oct 29, 2024 · Specifically, I need to calculate the loss grouped by each metadata category (e. 57 minutes ago · Tras darse a conocer que la actriz Jessica Díaz habría muerto a los 34 años; Roger González dio la cara y reveló por qué publicó la polémica foto y cómo enfrentó el rumor que desató. My problem: I want to stepwise print/save the loss and accuracy of my training set by using the Trainer. Simplified, it looks like this: model = BertForSequenceClassification. 2w次，点赞34次，收藏30次。当使用transformers的Trainer进行模型训练时，若需自定义评价指标，可以通过在TrainingArguments中设置label_names、remove_unused_columns和include_inputs_for_metrics参数来保留和访问自定义数据。在compute_metrics方法中，可以访问到label_ids中的自定义列数据进行计算。 peft_config (Dict, defaults to None) — The PEFT configuration to use for training. Overall, pros crush cons for me. As there are very few examples online on how to use Huggingface’s Trainer API, I hope to contribute a simple example of how Trainer could be used to fine-tune your pretrained model. While training and evaluating we record the following reward metrics: global_step: The total number of optimizer steps taken so far. train() Any help appreciated.

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