Ability to save model outcomes in tabular format CSV file?
I am downloading the model https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384/tree/main microsoft/Multilingual-MiniLM-L12-H384 and then using it.

Transformer Version: '4.11.3'

I have written the below code:

```
model = tr.BertForSequenceClassification.from_pretrained("/home/pc/minilm_model",num_labels=2)
model.to(device)

print("hello")

training_args = tr.TrainingArguments(
    output_dir='/home/pc/proj/results2',          # output directory
    num_train_epochs=10,              # total number of training epochs
    per_device_train_batch_size=16,  # batch size per device during training
    per_device_eval_batch_size=32,   # batch size for evaluation
    learning_rate=2e-5,
    warmup_steps=1000,                # number of warmup steps for learning rate scheduler
    weight_decay=0.01,               # strength of weight decay
    logging_dir='./logs',            # directory for storing logs
    logging_steps=1000,
    evaluation_strategy="epoch",
    save_strategy="no"
)

print("hello")

trainer = tr.Trainer(
    model=model,                         # the instantiated 🤗 Transformers model to be trained
    args=training_args,                  # training arguments, defined above
    train_dataset=train_data,         # training dataset
    eval_dataset=val_data,             # evaluation dataset
    compute_metrics=compute_metrics
)

```
Is there way to retrieve my ( **I do not want to use tensor-board**) :

1. **Training loss** for every epoch
2. **Validation loss** for every epoch

In a tabular format ( May be in CSV file)

Then I want to plot my train and validation loss graph.

**Please help me what changes do I need to bring in the above code in case its feasible.**



You need to add your own logging handler.
Check this: https://github.com/huggingface/transformers/issues/10454<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.