diff --git a/training/Dockerfile b/training/Dockerfile
index 098132c..c56480f 100644
--- a/training/Dockerfile
+++ b/training/Dockerfile
@@ -2,7 +2,7 @@
 # ARG COMPAT=0
 ARG PERSONAL=0
 # FROM nvidia/cuda:11.3.1-devel-ubuntu20.04 as base-0
-FROM nvcr.io/nvidia/pytorch:22.11-py3 as base
+FROM nvcr.io/nvidia/pytorch:22.12-py3 as base
 
 ENV HOST docker
 ENV LANG=C.UTF-8 LC_ALL=C.UTF-8
@@ -67,30 +67,29 @@ ENV PIP_NO_CACHE_DIR=1
 # RUN pip install --upgrade --force-reinstall --global-option="--cpp_ext" --global-option="--cuda_ext" --global-option="--fast_multihead_attn" --global-option="--fmha" --global-option="--fast_layer_norm" --global-option="--xentropy" git+https://github.com/NVIDIA/apex.git#egg=apex
 
 # xgboost conflicts with deepspeed
-RUN pip uninstall -y xgboost && DS_BUILD_UTILS=1 DS_BUILD_FUSED_LAMB=1 pip install deepspeed==0.7.5
+RUN pip uninstall -y xgboost && DS_BUILD_UTILS=1 DS_BUILD_FUSED_LAMB=1 pip install deepspeed==0.7.7
 
 # General packages that we don't care about the version
 # zstandard to extract the_pile dataset
 # psutil to get the number of cpu physical cores
 # twine to upload package to PyPI
-# ninja is broken for some reason, it returns error code 245
-RUN pip uninstall -y ninja && pip install ninja
-RUN pip install pytest matplotlib jupyter ipython ipdb gpustat scikit-learn spacy munch einops opt_einsum fvcore gsutil cmake pykeops zstandard psutil h5py twine \
+RUN pip install pytest matplotlib jupyter ipython ipdb gpustat scikit-learn spacy munch einops opt_einsum fvcore gsutil cmake pykeops zstandard psutil h5py twine gdown \
     && python -m spacy download en_core_web_sm
 # hydra
-RUN pip install hydra-core==1.2.0 hydra-colorlog==1.2.0 hydra-optuna-sweeper==1.2.0 pyrootutils rich
+RUN pip install hydra-core==1.3.1 hydra-colorlog==1.2.0 hydra-optuna-sweeper==1.2.0 pyrootutils rich
 # Core packages
-RUN pip install transformers==4.24.0 datasets==2.7.1 pytorch-lightning==1.7.7 triton==2.0.0.dev20221120 wandb==0.13.5 timm==0.6.12 torchmetrics==0.10.3
+RUN pip install transformers==4.25.1 datasets==2.8.0 pytorch-lightning==1.8.6 triton==2.0.0.dev20221202 wandb==0.13.7 timm==0.6.12 torchmetrics==0.11.0
 
 # For MLPerf
 RUN pip install git+https://github.com/mlcommons/logging.git@2.1.0
 
 # Install FlashAttention
-RUN pip install flash-attn==0.2.2
+RUN pip install flash-attn==0.2.6.post
 
 # Install CUDA extensions for cross-entropy, fused dense, layer norm
-RUN git clone https://github.com/HazyResearch/flash-attention \
-    && cd flash-attention && git checkout v0.2.2 \
+# Install CUDA extensions for cross-entropy, fused dense, layer norm
+    RUN git clone https://github.com/HazyResearch/flash-attention \
+    && cd flash-attention && git checkout v0.2.6 \
     && cd csrc/fused_softmax && pip install . && cd ../../ \
     && cd csrc/rotary && pip install . && cd ../../ \
     && cd csrc/xentropy && pip install . && cd ../../ \