Repository: transformers
Issue: KeyError: 'labels' during Distilling Zero Shot Classification
Labels: Good Second Issue

EDIT: I confirmed that this happens with the example script as it is, so no other changes are required to reproduce this.

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->

- `transformers` version: 4.6.1
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.1+cu101 (True)
- Tensorflow version (GPU?): 2.5.0 (True)
- Using GPU in script?: Yes (NVIDIA P100)
- Using distributed or parallel set-up in script?: No


### Who can help

Tagging @VictorSanh @sgugger, @patil-suraj (please correct me if I'm wrong)

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Models:

- albert, bert, xlm: @LysandreJik
- blenderbot, bart, marian, pegasus, encoderdecoder,  t5: @patrickvonplaten, @patil-suraj
- longformer, reformer, transfoxl, xlnet: @patrickvonplaten
- fsmt: @stas00
- funnel: @sgugger
- gpt2: @patrickvonplaten, @LysandreJik
- rag: @patrickvonplaten, @lhoestq
- tensorflow: @Rocketknight1

Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam
- text generation: @patrickvonplaten
- tokenizers: @LysandreJik
- trainer: @sgugger
- pipelines: @LysandreJik

Documentation: @sgugger

Model hub:

- for issues with a model report at https://discuss.huggingface.co/ and tag the model's creator.

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Examples:

- maintained examples (not research project or legacy): @sgugger, @patil-suraj
- research_projects/bert-loses-patience: @JetRunner
- research_projects/distillation: @VictorSanh

 -->

## Information

Model I am using (Bert, XLNet ...):

Student: `distilbert-base-uncased`
Teacher: `roberta-large-mnli`

The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [ ] my own task or dataset: (give details below)
* [x] other: distillation of zero shot text classification models (research_projects)

I'm simply running the official colab script `Distilling Zero Shot Classification.ipynb`, but get a key error when performing the first epoch of the student training.

## To reproduce

Steps to reproduce the behavior:

1. Open the official script https://t.co/JAJ6Eb78vM?amp=1 (you can find this link here as well https://twitter.com/joeddav/status/1363543296166002688?lang=en)
2. Run all the required cells before training
3. Run the cell that runs `transformers/examples/research_projects/zero-shot-distillation/distill_classifier.py`
4. Witness the `KeyError: 'labels'` on the first epoch of the student model training

Full logs:

`2021-06-16 15:33:19.328924: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0
06/16/2021 15:33:20 - WARNING - __main__ -   Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False
06/16/2021 15:33:20 - INFO - __main__ -   Training/evaluation parameters DistillTrainingArguments(output_dir='./distilbert-base-uncased-agnews-student', overwrite_output_dir=False, do_train=True, do_eval=True, do_predict=False, evaluation_strategy=<IntervalStrategy.NO: 'no'>, prediction_loss_only=False, per_device_train_batch_size=32, per_device_eval_batch_size=128, per_gpu_train_batch_size=None, per_gpu_eval_batch_size=None, gradient_accumulation_steps=1, eval_accumulation_steps=None, learning_rate=5e-05, weight_decay=0.0, adam_beta1=0.9, adam_beta2=0.999, adam_epsilon=1e-08, max_grad_norm=1.0, num_train_epochs=1.0, max_steps=-1, lr_scheduler_type=<SchedulerType.LINEAR: 'linear'>, warmup_ratio=0.0, warmup_steps=0, logging_dir='runs/Jun16_15-33-20_9d2a3f891a99', logging_strategy=<IntervalStrategy.STEPS: 'steps'>, logging_first_step=False, logging_steps=500, save_strategy=<IntervalStrategy.STEPS: 'steps'>, save_steps=500, save_total_limit=0, no_cuda=False, seed=42, fp16=False, fp16_opt_level='O1', fp16_backend='auto', fp16_full_eval=False, local_rank=-1, tpu_num_cores=None, tpu_metrics_debug=False, debug=[], dataloader_drop_last=False, eval_steps=500, dataloader_num_workers=0, past_index=-1, run_name='./distilbert-base-uncased-agnews-student', disable_tqdm=False, remove_unused_columns=True, label_names=None, load_best_model_at_end=False, metric_for_best_model=None, greater_is_better=None, ignore_data_skip=False, sharded_ddp=[], deepspeed=None, label_smoothing_factor=0.0, adafactor=False, group_by_length=False, length_column_name='length', report_to=['tensorboard'], ddp_find_unused_parameters=None, dataloader_pin_memory=True, skip_memory_metrics=False, use_legacy_prediction_loop=False, push_to_hub=False, resume_from_checkpoint=None, mp_parameters='')
06/16/2021 15:33:20 - INFO - __main__ -   Generating predictions from zero-shot teacher model
[INFO|configuration_utils.py:517] 2021-06-16 15:33:21,219 >> loading configuration file https://huggingface.co/roberta-large-mnli/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/fab42bdbd5cb5e6ff7cabeb9bcc12728f56022f50b9644a3079904564f2bc704.ddc5961cccf081d6ca7f4f58ee119c21895aa9b19f0044f01954cd2ff42fefcb
[INFO|configuration_utils.py:553] 2021-06-16 15:33:21,220 >> Model config RobertaConfig {
  "_num_labels": 3,
  "architectures": [
    "RobertaForSequenceClassification"
  ],
  "attention_probs_dropout_prob": 0.1,
  "bos_token_id": 0,
  "eos_token_id": 2,
  "gradient_checkpointing": false,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.1,
  "hidden_size": 1024,
  "id2label": {
    "0": "CONTRADICTION",
    "1": "NEUTRAL",
    "2": "ENTAILMENT"
  },
  "initializer_range": 0.02,
  "intermediate_size": 4096,
  "label2id": {
    "CONTRADICTION": 0,
    "ENTAILMENT": 2,
    "NEUTRAL": 1
  },
  "layer_norm_eps": 1e-05,
  "max_position_embeddings": 514,
  "model_type": "roberta",
  "num_attention_heads": 16,
  "num_hidden_layers": 24,
  "pad_token_id": 1,
  "position_embedding_type": "absolute",
  "transformers_version": "4.6.1",
  "type_vocab_size": 1,
  "use_cache": true,
  "vocab_size": 50265
}

[INFO|modeling_utils.py:1155] 2021-06-16 15:33:21,507 >> loading weights file https://huggingface.co/roberta-large-mnli/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/63cbd98723b89863bcd86a8002e823de3004a139513559246690c65521cdc9b9.38ef55c51c84ab2e78e5a0e2ea9c25830fd074df70d2f10071eb9a1bc1586ca0
[WARNING|modeling_utils.py:1331] 2021-06-16 15:33:44,205 >> Some weights of the model checkpoint at roberta-large-mnli were not used when initializing RobertaForSequenceClassification: ['roberta.pooler.dense.weight', 'roberta.pooler.dense.bias']
- This IS expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
[INFO|modeling_utils.py:1348] 2021-06-16 15:33:44,205 >> All the weights of RobertaForSequenceClassification were initialized from the model checkpoint at roberta-large-mnli.
If your task is similar to the task the model of the checkpoint was trained on, you can already use RobertaForSequenceClassification for predictions without further training.
[INFO|configuration_utils.py:517] 2021-06-16 15:33:47,683 >> loading configuration file https://huggingface.co/roberta-large-mnli/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/fab42bdbd5cb5e6ff7cabeb9bcc12728f56022f50b9644a3079904564f2bc704.ddc5961cccf081d6ca7f4f58ee119c21895aa9b19f0044f01954cd2ff42fefcb
[INFO|configuration_utils.py:553] 2021-06-16 15:33:47,684 >> Model config RobertaConfig {
  "_num_labels": 3,
  "architectures": [
    "RobertaForSequenceClassification"
  ],
  "attention_probs_dropout_prob": 0.1,
  "bos_token_id": 0,
  "eos_token_id": 2,
  "gradient_checkpointing": false,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.1,
  "hidden_size": 1024,
  "id2label": {
    "0": "CONTRADICTION",
    "1": "NEUTRAL",
    "2": "ENTAILMENT"
  },
  "initializer_range": 0.02,
  "intermediate_size": 4096,
  "label2id": {
    "CONTRADICTION": 0,
    "ENTAILMENT": 2,
    "NEUTRAL": 1
  },
  "layer_norm_eps": 1e-05,
  "max_position_embeddings": 514,
  "model_type": "roberta",
  "num_attention_heads": 16,
  "num_hidden_layers": 24,
  "pad_token_id": 1,
  "position_embedding_type": "absolute",
  "transformers_version": "4.6.1",
  "type_vocab_size": 1,
  "use_cache": true,
  "vocab_size": 50265
}

[INFO|tokenization_utils_base.py:1717] 2021-06-16 15:33:49,522 >> loading file https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json from cache at /root/.cache/huggingface/transformers/64a1d72b2bd05b0aff1a4dd9e7a90a6eea0312b4f914e80b0a923aa8f72219bd.d67d6b367eb24ab43b08ad55e014cf254076934f71d832bbab9ad35644a375ab
[INFO|tokenization_utils_base.py:1717] 2021-06-16 15:33:49,522 >> loading file https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt from cache at /root/.cache/huggingface/transformers/425529714b758f50b6d3f93f8093d859856fd41cf1cec7c8edf2ab44aee632b6.5d12962c5ee615a4c803841266e9c3be9a691a924f72d395d3a6c6c81157788b
[INFO|tokenization_utils_base.py:1717] 2021-06-16 15:33:49,522 >> loading file https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/d077eac6b48c43618a441cba6eab600a5cc6383b98e7eada6d1ad4d3f3cc457e.fc9576039592f026ad76a1c231b89aee8668488c671dfbe6616bab2ed298d730
[INFO|tokenization_utils_base.py:1717] 2021-06-16 15:33:49,522 >> loading file https://huggingface.co/roberta-large-mnli/resolve/main/added_tokens.json from cache at None
[INFO|tokenization_utils_base.py:1717] 2021-06-16 15:33:49,522 >> loading file https://huggingface.co/roberta-large-mnli/resolve/main/special_tokens_map.json from cache at None
[INFO|tokenization_utils_base.py:1717] 2021-06-16 15:33:49,522 >> loading file https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer_config.json from cache at None
100% 15000/15000 [1:15:16<00:00,  3.32it/s]
06/16/2021 16:49:06 - INFO - __main__ -   Initializing student model
[INFO|file_utils.py:1532] 2021-06-16 16:49:07,106 >> https://huggingface.co/distilbert-base-uncased/resolve/main/config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpy7f4tyyh
Downloading: 100% 442/442 [00:00<00:00, 348kB/s]
[INFO|file_utils.py:1536] 2021-06-16 16:49:07,540 >> storing https://huggingface.co/distilbert-base-uncased/resolve/main/config.json in cache at /root/.cache/huggingface/transformers/23454919702d26495337f3da04d1655c7ee010d5ec9d77bdb9e399e00302c0a1.d423bdf2f58dc8b77d5f5d18028d7ae4a72dcfd8f468e81fe979ada957a8c361
[INFO|file_utils.py:1544] 2021-06-16 16:49:07,540 >> creating metadata file for /root/.cache/huggingface/transformers/23454919702d26495337f3da04d1655c7ee010d5ec9d77bdb9e399e00302c0a1.d423bdf2f58dc8b77d5f5d18028d7ae4a72dcfd8f468e81fe979ada957a8c361
[INFO|configuration_utils.py:517] 2021-06-16 16:49:07,540 >> loading configuration file https://huggingface.co/distilbert-base-uncased/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/23454919702d26495337f3da04d1655c7ee010d5ec9d77bdb9e399e00302c0a1.d423bdf2f58dc8b77d5f5d18028d7ae4a72dcfd8f468e81fe979ada957a8c361
[INFO|configuration_utils.py:553] 2021-06-16 16:49:07,541 >> Model config DistilBertConfig {
  "activation": "gelu",
  "architectures": [
    "DistilBertForMaskedLM"
  ],
  "attention_dropout": 0.1,
  "dim": 768,
  "dropout": 0.1,
  "hidden_dim": 3072,
  "id2label": {
    "0": "LABEL_0",
    "1": "LABEL_1",
    "2": "LABEL_2",
    "3": "LABEL_3"
  },
  "initializer_range": 0.02,
  "label2id": {
    "LABEL_0": 0,
    "LABEL_1": 1,
    "LABEL_2": 2,
    "LABEL_3": 3
  },
  "max_position_embeddings": 512,
  "model_type": "distilbert",
  "n_heads": 12,
  "n_layers": 6,
  "pad_token_id": 0,
  "qa_dropout": 0.1,
  "seq_classif_dropout": 0.2,
  "sinusoidal_pos_embds": false,
  "tie_weights_": true,
  "transformers_version": "4.6.1",
  "vocab_size": 30522
}

[INFO|file_utils.py:1532] 2021-06-16 16:49:07,820 >> https://huggingface.co/distilbert-base-uncased/resolve/main/pytorch_model.bin not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmptuo3f4g2
Downloading: 100% 268M/268M [00:04<00:00, 62.4MB/s]
[INFO|file_utils.py:1536] 2021-06-16 16:49:12,343 >> storing https://huggingface.co/distilbert-base-uncased/resolve/main/pytorch_model.bin in cache at /root/.cache/huggingface/transformers/9c169103d7e5a73936dd2b627e42851bec0831212b677c637033ee4bce9ab5ee.126183e36667471617ae2f0835fab707baa54b731f991507ebbb55ea85adb12a
[INFO|file_utils.py:1544] 2021-06-16 16:49:12,343 >> creating metadata file for /root/.cache/huggingface/transformers/9c169103d7e5a73936dd2b627e42851bec0831212b677c637033ee4bce9ab5ee.126183e36667471617ae2f0835fab707baa54b731f991507ebbb55ea85adb12a
[INFO|modeling_utils.py:1155] 2021-06-16 16:49:12,343 >> loading weights file https://huggingface.co/distilbert-base-uncased/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/9c169103d7e5a73936dd2b627e42851bec0831212b677c637033ee4bce9ab5ee.126183e36667471617ae2f0835fab707baa54b731f991507ebbb55ea85adb12a
[WARNING|modeling_utils.py:1331] 2021-06-16 16:49:12,787 >> Some weights of the model checkpoint at distilbert-base-uncased were not used when initializing DistilBertForSequenceClassification: ['vocab_layer_norm.bias', 'vocab_transform.weight', 'vocab_transform.bias', 'vocab_layer_norm.weight', 'vocab_projector.bias', 'vocab_projector.weight']
- This IS expected if you are initializing DistilBertForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing DistilBertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
[WARNING|modeling_utils.py:1342] 2021-06-16 16:49:12,787 >> Some weights of DistilBertForSequenceClassification were not initialized from the model checkpoint at distilbert-base-uncased and are newly initialized: ['pre_classifier.bias', 'classifier.bias', 'pre_classifier.weight', 'classifier.weight']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
[INFO|configuration_utils.py:517] 2021-06-16 16:49:13,073 >> loading configuration file https://huggingface.co/distilbert-base-uncased/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/23454919702d26495337f3da04d1655c7ee010d5ec9d77bdb9e399e00302c0a1.d423bdf2f58dc8b77d5f5d18028d7ae4a72dcfd8f468e81fe979ada957a8c361
[INFO|configuration_utils.py:553] 2021-06-16 16:49:13,074 >> Model config DistilBertConfig {
  "activation": "gelu",
  "architectures": [
    "DistilBertForMaskedLM"
  ],
  "attention_dropout": 0.1,
  "dim": 768,
  "dropout": 0.1,
  "hidden_dim": 3072,
  "initializer_range": 0.02,
  "max_position_embeddings": 512,
  "model_type": "distilbert",
  "n_heads": 12,
  "n_layers": 6,
  "pad_token_id": 0,
  "qa_dropout": 0.1,
  "seq_classif_dropout": 0.2,
  "sinusoidal_pos_embds": false,
  "tie_weights_": true,
  "transformers_version": "4.6.1",
  "vocab_size": 30522
}

[INFO|file_utils.py:1532] 2021-06-16 16:49:13,357 >> https://huggingface.co/distilbert-base-uncased/resolve/main/vocab.txt not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmps3o1_gw9
Downloading: 100% 232k/232k [00:00<00:00, 1.83MB/s]
[INFO|file_utils.py:1536] 2021-06-16 16:49:13,766 >> storing https://huggingface.co/distilbert-base-uncased/resolve/main/vocab.txt in cache at /root/.cache/huggingface/transformers/0e1bbfda7f63a99bb52e3915dcf10c3c92122b827d92eb2d34ce94ee79ba486c.d789d64ebfe299b0e416afc4a169632f903f693095b4629a7ea271d5a0cf2c99
[INFO|file_utils.py:1544] 2021-06-16 16:49:13,766 >> creating metadata file for /root/.cache/huggingface/transformers/0e1bbfda7f63a99bb52e3915dcf10c3c92122b827d92eb2d34ce94ee79ba486c.d789d64ebfe299b0e416afc4a169632f903f693095b4629a7ea271d5a0cf2c99
[INFO|file_utils.py:1532] 2021-06-16 16:49:14,049 >> https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmp1n0mi2iy
Downloading: 100% 466k/466k [00:00<00:00, 3.48MB/s]
[INFO|file_utils.py:1536] 2021-06-16 16:49:14,616 >> storing https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer.json in cache at /root/.cache/huggingface/transformers/75abb59d7a06f4f640158a9bfcde005264e59e8d566781ab1415b139d2e4c603.7f2721073f19841be16f41b0a70b600ca6b880c8f3df6f3535cbc704371bdfa4
[INFO|file_utils.py:1544] 2021-06-16 16:49:14,616 >> creating metadata file for /root/.cache/huggingface/transformers/75abb59d7a06f4f640158a9bfcde005264e59e8d566781ab1415b139d2e4c603.7f2721073f19841be16f41b0a70b600ca6b880c8f3df6f3535cbc704371bdfa4
[INFO|file_utils.py:1532] 2021-06-16 16:49:15,461 >> https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer_config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmperm21jrj
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[INFO|file_utils.py:1536] 2021-06-16 16:49:15,745 >> storing https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer_config.json in cache at /root/.cache/huggingface/transformers/8c8624b8ac8aa99c60c912161f8332de003484428c47906d7ff7eb7f73eecdbb.20430bd8e10ef77a7d2977accefe796051e01bc2fc4aa146bc862997a1a15e79
[INFO|file_utils.py:1544] 2021-06-16 16:49:15,745 >> creating metadata file for /root/.cache/huggingface/transformers/8c8624b8ac8aa99c60c912161f8332de003484428c47906d7ff7eb7f73eecdbb.20430bd8e10ef77a7d2977accefe796051e01bc2fc4aa146bc862997a1a15e79
[INFO|tokenization_utils_base.py:1717] 2021-06-16 16:49:15,746 >> loading file https://huggingface.co/distilbert-base-uncased/resolve/main/vocab.txt from cache at /root/.cache/huggingface/transformers/0e1bbfda7f63a99bb52e3915dcf10c3c92122b827d92eb2d34ce94ee79ba486c.d789d64ebfe299b0e416afc4a169632f903f693095b4629a7ea271d5a0cf2c99
[INFO|tokenization_utils_base.py:1717] 2021-06-16 16:49:15,746 >> loading file https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer.json from cache at /root/.cache/huggingface/transformers/75abb59d7a06f4f640158a9bfcde005264e59e8d566781ab1415b139d2e4c603.7f2721073f19841be16f41b0a70b600ca6b880c8f3df6f3535cbc704371bdfa4
[INFO|tokenization_utils_base.py:1717] 2021-06-16 16:49:15,746 >> loading file https://huggingface.co/distilbert-base-uncased/resolve/main/added_tokens.json from cache at None
[INFO|tokenization_utils_base.py:1717] 2021-06-16 16:49:15,746 >> loading file https://huggingface.co/distilbert-base-uncased/resolve/main/special_tokens_map.json from cache at None
[INFO|tokenization_utils_base.py:1717] 2021-06-16 16:49:15,746 >> loading file https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer_config.json from cache at /root/.cache/huggingface/transformers/8c8624b8ac8aa99c60c912161f8332de003484428c47906d7ff7eb7f73eecdbb.20430bd8e10ef77a7d2977accefe796051e01bc2fc4aa146bc862997a1a15e79
100% 120000/120000 [00:32<00:00, 3647.18ex/s]
06/16/2021 16:49:49 - INFO - __main__ -   Training student model on teacher predictions
[INFO|trainer.py:516] 2021-06-16 16:49:49,272 >> The following columns in the training set  don't have a corresponding argument in `DistilBertForSequenceClassification.forward` and have been ignored: text.
[INFO|trainer.py:1156] 2021-06-16 16:49:49,285 >> ***** Running training *****
[INFO|trainer.py:1157] 2021-06-16 16:49:49,285 >>   Num examples = 120000
[INFO|trainer.py:1158] 2021-06-16 16:49:49,285 >>   Num Epochs = 1
[INFO|trainer.py:1159] 2021-06-16 16:49:49,285 >>   Instantaneous batch size per device = 32
[INFO|trainer.py:1160] 2021-06-16 16:49:49,285 >>   Total train batch size (w. parallel, distributed & accumulation) = 32
[INFO|trainer.py:1161] 2021-06-16 16:49:49,285 >>   Gradient Accumulation steps = 1
[INFO|trainer.py:1162] 2021-06-16 16:49:49,286 >>   Total optimization steps = 3750
  0% 0/3750 [00:00<?, ?it/s]Traceback (most recent call last):
  File "transformers/examples/research_projects/zero-shot-distillation/distill_classifier.py", line 338, in <module>
    main()
  File "transformers/examples/research_projects/zero-shot-distillation/distill_classifier.py", line 328, in main
    trainer.train()
  File "/usr/local/lib/python3.7/dist-packages/transformers/trainer.py", line 1272, in train
    tr_loss += self.training_step(model, inputs)
  File "/usr/local/lib/python3.7/dist-packages/transformers/trainer.py", line 1734, in training_step
    loss = self.compute_loss(model, inputs)
  File "transformers/examples/research_projects/zero-shot-distillation/distill_classifier.py", line 119, in compute_loss
    target_p = inputs["labels"]
KeyError: 'labels'
  0% 0/3750 [00:00<?, ?it/s]
`

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## Expected behavior

Not throw a `KeyError`

<!-- A clear and concise description of what you would expect to happen. -->