# Train results for text classification

**URL:** <https://discuss.huggingface.co/t/train-results-for-text-classification/63099>\
**Category:** 🤗Transformers\
**Created:** [November 22, 2023, 6:30am UTC](https://discuss.huggingface.co/t/train-results-for-text-classification/63099 "2023-11-22T06:30:10Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![vekapex](https://avatars.discourse-cdn.com/v4/letter/v/96bed5/32.png) [@vekapex](https://discuss.huggingface.co/u/vekapex)\
**Post date:** [November 22, 2023, 6:30am UTC](https://discuss.huggingface.co/t/train-results-for-text-classification/63099/1 "2023-11-22T06:30:10Z")

</div>

I’m trying to get train results for text classification ([https://github.com/huggingface/transformers/blob/main/examples/flax/text-classification](https://github.com/huggingface/transformers/blob/main/examples/flax/text-classification))  
using the following cmd:

```auto
export TASK_NAME=mrpc

python run_flax_glue.py \
  --model_name_or_path bert-base-cased \
  --task_name ${TASK_NAME} \
  --max_seq_length 128 \
  --learning_rate 2e-5 \
  --num_train_epochs 3 \
  --per_device_train_batch_size 4 \
  --eval_steps 100 \
  --output_dir ./$TASK_NAME/ \
  --evaluation_strategy epoch \
  --logging_dir ./$TASK_NAME/ \
  --logging_strategy epoch \
  --train_file ./$TASK_NAME/train.json \
  --overwrite_output_dir \
  --logging_steps 10 \
  --do_train \
  --do_eval

```

Unfortunately output folder does not contain expected `train_results.json` (like here [How to monitor both train and validation metrics at the same step? - #13 by lewtun](https://discuss.huggingface.co/t/how-to-monitor-both-train-and-validation-metrics-at-the-same-step/1301/13)). In my case, the output folder is as follows:

```auto
drwxrwxr-x 2 root root 180 Nov 21 21:23 ./
drwxrwxr-x 3 root root 140 Nov 21 21:41 ../
-rw-rw-r-- 1 root root 682 Nov 21 21:42 config.json
-rw-rw-r-- 1 root root 78 Nov 21 21:42 eval_results.json
-rw-rw-r-- 1 root root 433254456 Nov 21 21:42 flax_model.msgpack
-rw-rw-r-- 1 root root 125 Nov 21 21:42 special_tokens_map.json
-rw-rw-r-- 1 root root 669188 Nov 21 21:42 tokenizer.json
-rw-rw-r-- 1 root root 1191 Nov 21 21:42 tokenizer_config.json
-rw-rw-r-- 1 root root 213450 Nov 21 21:42 vocab.txt

```

Any hint/advice how to get train results for this model?