# Getting error when fine-tuning Transformer model: Expected sequence or array-like, got \ **URL:** \ **Category:** Beginners\ **Created:** [December 27, 2022, 2:27pm UTC](https://discuss.huggingface.co/t/getting-error-when-fine-tuning-transformer-model-expected-sequence-or-array-like-got-class-transformers-trainer-utils-evalprediction/28515 "2022-12-27T14:27:12Z")\ **Posts on this page:** 1\ **Page:** 1
**Author:** ![hassanashas](https://avatars.discourse-cdn.com/v4/letter/h/59ef9b/32.png) [@hassanashas](https://discuss.huggingface.co/u/hassanashas)\ **Post date:** [December 27, 2022, 2:27pm UTC](https://discuss.huggingface.co/t/getting-error-when-fine-tuning-transformer-model-expected-sequence-or-array-like-got-class-transformers-trainer-utils-evalprediction/28515/1 "2022-12-27T14:27:12Z")
Hi, I am trying to implement Model from Hugging Face transformer library following this Youtube video: [Simple Training with the 🤗 Transformers Trainer - YouTube](https://www.youtube.com/watch?v=u--UVvH-LIQ) I have followed along all the steps but for some reason, I get an error when I try to execute the **trainer.train() command**. This is the error I am getting, `TypeError: Expected sequence or array-like, got ` Full error details are as follows, ```auto The following columns in the evaluation set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: label_text, text. If label_text, text are not expected by `BertForSequenceClassification.forward`, you can safely ignore this message. *****Running Evaluation***** Num examples = 2000 Batch size = 64 --------------------------------------------------------------------------- TypeError Traceback (most recent call last) in ----> 1 trainer.train() 13 frames /usr/local/lib/python3.8/dist-packages/sklearn/utils/validation.py in _num_samples(x) 263 x = np.asarray(x) 264 else: --> 265 raise TypeError(message) 266 267 if hasattr(x, "shape") and x.shape is not None: TypeError: Expected sequence or array-like, got ``` Anyone who knows what could be the possible reason behind this error? If needed, you can access my Google Colab Notebook here. The Colab Notebook contains all the code that I did (it is same as the code shown in the video): **[Google Colab](https://colab.research.google.com/drive/1-4QuKsqe-w0EBA95D-gz8ch3l3FytVpX?usp=sharing)** If you would like to know my training\_arguments and compute\_metrics function, then I am also sharing them below, ```auto def compute_metrics(pred): labels = pred.label_ids preds = pred.predictions.argmax(-1) f1 = f1_score(labels, pred, average='weighted') return {"f1": f1} ``` ```auto batch_size = 64 logging_steps = len(emotion_dataset['train']) output_dir = "minlm-finetuned-emotion" training_args = TrainingArguments(output_dir = output_dir, num_train_epochs=5, learning_rate=2e-5, per_device_train_batch_size=batch_size, per_device_eval_batch_size=batch_size, weight_decay=0.01, evaluation_strategy="epoch", logging_steps=logging_steps, fp16=True, push_to_hub=True ) ``` ```auto trainer = WeightedLossTrainer(model=model, args=training_args, compute_metrics=compute_metrics, train_dataset=emotion_dataset['train'], eval_dataset=emotion_dataset['validation'], tokenizer=tokenizer) ``` ```auto trainer.train() ```