Revert "Add a template for examples and apply it for mlm and plm exam…

…ples (huggingface#8153)"

This reverts commit 72f8bd1.

.circleci/config.yml

@@ -320,9 +320,9 @@ jobs:
                   key: v0.4-code_quality-{{ checksum "setup.py" }}
                   paths:
                       - '~/.cache/pip'
-            - run: black --check examples tests src utils
-            - run: isort --check-only examples tests src utils
-            - run: flake8 examples tests src utils
+            - run: black --check examples templates tests src utils
+            - run: isort --check-only examples templates tests src utils
+            - run: flake8 examples templates tests src utils
             - run: python utils/style_doc.py src/transformers docs/source --max_len 119 --check_only
             - run: python utils/check_copies.py
             - run: python utils/check_dummies.py

Makefile

@@ -1,7 +1,7 @@
 .PHONY: modified_only_fixup extra_quality_checks quality style fixup fix-copies test test-examples docs
 
 
-check_dirs := examples tests src utils
+check_dirs := examples templates tests src utils
 
 # get modified files since the branch was made
 fork_point_sha := $(shell git merge-base --fork-point master)

examples/language-modeling/run_clm.py

@@ -18,7 +18,7 @@
 Here is the full list of checkpoints on the hub that can be fine-tuned by this script:
 https://huggingface.co/models?filter=causal-lm
 """
-# You can also adapt this script on your own causal language modeling task. Pointers for this are left as comments.
+# You can also adapt this script on your own text classification task. Pointers for this are left as comments.
 
 import logging
 import math
@@ -325,7 +325,7 @@ def group_texts(examples):
         perplexity = math.exp(eval_output["eval_loss"])
         results["perplexity"] = perplexity
 
-        output_eval_file = os.path.join(training_args.output_dir, "eval_results_clm.txt")
+        output_eval_file = os.path.join(training_args.output_dir, "eval_results_lm.txt")
         if trainer.is_world_process_zero():
             with open(output_eval_file, "w") as writer:
                 logger.info("***** Eval results *****")