Saving weights and logs of step 10

config.py

@@ -1,6 +1,6 @@
 from transformers import GPT2Config
 
-model_dir = "sinhala-gpt2"
+model_dir = "./sihala-gpt2"
 
 config = GPT2Config.from_pretrained("gpt2", resid_pdrop=0.0, embd_pdrop=0.0, attn_pdrop=0.0)
 config.save_pretrained(model_dir)

sinhala-gpt2/events.out.tfevents.1625744111.t1v-n-0b4afe6c-w-0.150137.3.v2 → events.out.tfevents.1625851395.t1v-n-0b4afe6c-w-0.251724.3.v2

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b12e68ec0cd3b02868ebc860c979432f60155c4361886accc65778b5e12609cb
-size 11082215
+oid sha256:e497ce08418104de7651e94eb9dffb54daac6d986bc927df823d3b9d8a78ae45
+size 40

flax_model.msgpack

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:694fdb364154b16f66f557226c6f0006187a1fe305f6696be427aa8e7f634748
+size 497764120

run_clm_flax.py

@@ -1 +0,0 @@
-/home/Keshan/transformers/examples/flax/language-modeling/run_clm_flax.py

si_tokenizer.py

@@ -1,7 +1,7 @@
 from datasets import load_dataset
 from tokenizers import trainers, Tokenizer, normalizers, ByteLevelBPETokenizer
 
-model_dir = "./sinhala-gpt2"  # ${MODEL_DIR}
+model_dir = "sinhala-gpt2"  # ${MODEL_DIR}
 
 # load dataset
 dataset = load_dataset("mc4", "si", split="train")